Overview

Dataset statistics

Number of variables100
Number of observations150346
Missing cells10369206
Missing cells (%)69.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory114.7 MiB
Average record size in memory800.0 B

Variable types

Categorical20
Unsupported3
Numeric4
Boolean73

Alerts

attributes_Music_no_music has constant value ""Constant
attributes_DietaryRestrictions_kosher has constant value ""Constant
business_id has a high cardinality: 150346 distinct valuesHigh cardinality
city has a high cardinality: 1416 distinct valuesHigh cardinality
categories has a high cardinality: 83160 distinct valuesHigh cardinality
hours_Monday has a high cardinality: 1315 distinct valuesHigh cardinality
hours_Tuesday has a high cardinality: 1414 distinct valuesHigh cardinality
hours_Wednesday has a high cardinality: 1403 distinct valuesHigh cardinality
hours_Thursday has a high cardinality: 1462 distinct valuesHigh cardinality
hours_Friday has a high cardinality: 1538 distinct valuesHigh cardinality
hours_Saturday has a high cardinality: 1439 distinct valuesHigh cardinality
hours_Sunday has a high cardinality: 1291 distinct valuesHigh cardinality
attributes_BusinessAcceptsCreditCards is highly imbalanced (71.2%)Imbalance
attributes_CoatCheck is highly imbalanced (60.3%)Imbalance
attributes_RestaurantsTakeOut is highly imbalanced (58.6%)Imbalance
attributes_BusinessParking_garage is highly imbalanced (72.4%)Imbalance
attributes_BusinessParking_validated is highly imbalanced (92.1%)Imbalance
attributes_BusinessParking_valet is highly imbalanced (87.9%)Imbalance
attributes_WheelchairAccessible is highly imbalanced (52.7%)Imbalance
attributes_RestaurantsAttire is highly imbalanced (89.7%)Imbalance
attributes_Ambience_romantic is highly imbalanced (87.5%)Imbalance
attributes_Ambience_intimate is highly imbalanced (84.9%)Imbalance
attributes_Ambience_touristy is highly imbalanced (93.3%)Imbalance
attributes_Ambience_hipster is highly imbalanced (81.4%)Imbalance
attributes_Ambience_divey is highly imbalanced (76.5%)Imbalance
attributes_Ambience_trendy is highly imbalanced (65.2%)Imbalance
attributes_Ambience_upscale is highly imbalanced (91.2%)Imbalance
attributes_GoodForMeal_dessert is highly imbalanced (62.1%)Imbalance
attributes_GoodForMeal_latenight is highly imbalanced (70.0%)Imbalance
attributes_BusinessAcceptsBitcoin is highly imbalanced (82.1%)Imbalance
attributes_Music_dj is highly imbalanced (70.1%)Imbalance
attributes_Music_background_music is highly imbalanced (81.3%)Imbalance
attributes_Music_jukebox is highly imbalanced (60.1%)Imbalance
attributes_Music_video is highly imbalanced (97.7%)Imbalance
attributes_Music_karaoke is highly imbalanced (90.0%)Imbalance
attributes_DietaryRestrictions_halal is highly imbalanced (78.9%)Imbalance
attributes_ByAppointmentOnly has 108047 (71.9%) missing valuesMissing
attributes_BusinessAcceptsCreditCards has 30654 (20.4%) missing valuesMissing
hours_Monday has 35872 (23.9%) missing valuesMissing
hours_Tuesday has 29715 (19.8%) missing valuesMissing
hours_Wednesday has 26575 (17.7%) missing valuesMissing
hours_Thursday has 25148 (16.7%) missing valuesMissing
hours_Friday has 25347 (16.9%) missing valuesMissing
hours_Saturday has 39576 (26.3%) missing valuesMissing
attributes_BikeParking has 77788 (51.7%) missing valuesMissing
attributes_RestaurantsPriceRange2 has 65066 (43.3%) missing valuesMissing
attributes_CoatCheck has 144766 (96.3%) missing valuesMissing
attributes_RestaurantsTakeOut has 92594 (61.6%) missing valuesMissing
attributes_RestaurantsDelivery has 98012 (65.2%) missing valuesMissing
attributes_Caters has 110279 (73.4%) missing valuesMissing
attributes_WiFi has 93482 (62.2%) missing valuesMissing
attributes_BusinessParking_garage has 63461 (42.2%) missing valuesMissing
attributes_BusinessParking_street has 64872 (43.1%) missing valuesMissing
attributes_BusinessParking_validated has 63692 (42.4%) missing valuesMissing
attributes_BusinessParking_lot has 63830 (42.5%) missing valuesMissing
attributes_BusinessParking_valet has 61551 (40.9%) missing valuesMissing
attributes_WheelchairAccessible has 121420 (80.8%) missing valuesMissing
attributes_HappyHour has 135177 (89.9%) missing valuesMissing
attributes_OutdoorSeating has 103426 (68.8%) missing valuesMissing
attributes_HasTV has 105281 (70.0%) missing valuesMissing
attributes_RestaurantsReservations has 105387 (70.1%) missing valuesMissing
attributes_DogsAllowed has 132088 (87.9%) missing valuesMissing
hours_Sunday has 69174 (46.0%) missing valuesMissing
attributes_Alcohol has 107195 (71.3%) missing valuesMissing
attributes_GoodForKids has 96999 (64.5%) missing valuesMissing
attributes_RestaurantsAttire has 111129 (73.9%) missing valuesMissing
attributes_RestaurantsTableService has 130379 (86.7%) missing valuesMissing
attributes_RestaurantsGoodForGroups has 106197 (70.6%) missing valuesMissing
attributes_DriveThru has 143341 (95.3%) missing valuesMissing
attributes_NoiseLevel has 112392 (74.8%) missing valuesMissing
attributes_Ambience_romantic has 109954 (73.1%) missing valuesMissing
attributes_Ambience_intimate has 110860 (73.7%) missing valuesMissing
attributes_Ambience_touristy has 110265 (73.3%) missing valuesMissing
attributes_Ambience_hipster has 111021 (73.8%) missing valuesMissing
attributes_Ambience_divey has 112075 (74.5%) missing valuesMissing
attributes_Ambience_classy has 110211 (73.3%) missing valuesMissing
attributes_Ambience_trendy has 111945 (74.5%) missing valuesMissing
attributes_Ambience_upscale has 109534 (72.9%) missing valuesMissing
attributes_Ambience_casual has 108832 (72.4%) missing valuesMissing
attributes_GoodForMeal_dessert has 126155 (83.9%) missing valuesMissing
attributes_GoodForMeal_latenight has 125306 (83.3%) missing valuesMissing
attributes_GoodForMeal_lunch has 123957 (82.4%) missing valuesMissing
attributes_GoodForMeal_dinner has 122914 (81.8%) missing valuesMissing
attributes_GoodForMeal_brunch has 125160 (83.2%) missing valuesMissing
attributes_GoodForMeal_breakfast has 124021 (82.5%) missing valuesMissing
attributes_BusinessAcceptsBitcoin has 132919 (88.4%) missing valuesMissing
attributes_Smoking has 145793 (97.0%) missing valuesMissing
attributes_Music_dj has 143632 (95.5%) missing valuesMissing
attributes_Music_background_music has 143278 (95.3%) missing valuesMissing
attributes_Music_no_music has 143488 (95.4%) missing valuesMissing
attributes_Music_jukebox has 144158 (95.9%) missing valuesMissing
attributes_Music_live has 143613 (95.5%) missing valuesMissing
attributes_Music_video has 143276 (95.3%) missing valuesMissing
attributes_Music_karaoke has 144556 (96.1%) missing valuesMissing
attributes_GoodForDancing has 145718 (96.9%) missing valuesMissing
attributes_AcceptsInsurance has 144641 (96.2%) missing valuesMissing
attributes_BestNights_monday has 144663 (96.2%) missing valuesMissing
attributes_BestNights_tuesday has 144663 (96.2%) missing valuesMissing
attributes_BestNights_friday has 144663 (96.2%) missing valuesMissing
attributes_BestNights_wednesday has 144663 (96.2%) missing valuesMissing
attributes_BestNights_thursday has 144663 (96.2%) missing valuesMissing
attributes_BestNights_sunday has 144663 (96.2%) missing valuesMissing
attributes_BestNights_saturday has 144663 (96.2%) missing valuesMissing
attributes_BYOB has 145907 (97.0%) missing valuesMissing
attributes_Corkage has 146804 (97.6%) missing valuesMissing
attributes_BYOBCorkage has 148907 (99.0%) missing valuesMissing
attributes_HairSpecializesIn_straightperms has 149344 (99.3%) missing valuesMissing
attributes_HairSpecializesIn_coloring has 149311 (99.3%) missing valuesMissing
attributes_HairSpecializesIn_extensions has 149311 (99.3%) missing valuesMissing
attributes_HairSpecializesIn_africanamerican has 149344 (99.3%) missing valuesMissing
attributes_HairSpecializesIn_curly has 149311 (99.3%) missing valuesMissing
attributes_HairSpecializesIn_kids has 149311 (99.3%) missing valuesMissing
attributes_HairSpecializesIn_perms has 149311 (99.3%) missing valuesMissing
attributes_HairSpecializesIn_asian has 149344 (99.3%) missing valuesMissing
attributes_Open24Hours has 150307 (> 99.9%) missing valuesMissing
attributes_RestaurantsCounterService has 150327 (> 99.9%) missing valuesMissing
attributes_AgesAllowed has 150217 (99.9%) missing valuesMissing
attributes_DietaryRestrictions_dairy-free has 150316 (> 99.9%) missing valuesMissing
attributes_DietaryRestrictions_gluten-free has 150316 (> 99.9%) missing valuesMissing
attributes_DietaryRestrictions_vegan has 150316 (> 99.9%) missing valuesMissing
attributes_DietaryRestrictions_kosher has 150316 (> 99.9%) missing valuesMissing
attributes_DietaryRestrictions_halal has 150316 (> 99.9%) missing valuesMissing
attributes_DietaryRestrictions_soy-free has 150316 (> 99.9%) missing valuesMissing
attributes_DietaryRestrictions_vegetarian has 150316 (> 99.9%) missing valuesMissing
business_id is uniformly distributedUniform
business_id has unique valuesUnique
name is an unsupported type, check if it needs cleaning or further analysisUnsupported
address is an unsupported type, check if it needs cleaning or further analysisUnsupported
postal_code is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-03-07 15:39:21.813749
Analysis finished2023-03-07 15:39:50.491767
Duration28.68 seconds
Software versionydata-profiling vv4.0.0
Download configurationconfig.json

Variables

business_id
Categorical

HIGH CARDINALITY  UNIFORM  UNIQUE 

Distinct150346
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
Pns2l4eNsfO8kk83dixA6A
 
1
twx6DPOgaD9CN8wlt4Jcbg
 
1
ogyKKg_D4ioc6Ech_pKqfw
 
1
9D0aKRGsutg8S0ClIanmrA
 
1
_XV_ug_IUiJrGfMiJUqz-Q
 
1
Other values (150341)
150341 

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters3307612
Distinct characters64
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique150346 ?
Unique (%)100.0%

Sample

1st rowPns2l4eNsfO8kk83dixA6A
2nd rowmpf3x-BjTdTEA3yCZrAYPw
3rd rowtUFrWirKiKi_TAnsVWINQQ
4th rowMTSW4McQd7CbVtyjqoe9mw
5th rowmWMc6_wTdE0EUBKIGXDVfA

Common Values

ValueCountFrequency (%)
Pns2l4eNsfO8kk83dixA6A 1
 
< 0.1%
twx6DPOgaD9CN8wlt4Jcbg 1
 
< 0.1%
ogyKKg_D4ioc6Ech_pKqfw 1
 
< 0.1%
9D0aKRGsutg8S0ClIanmrA 1
 
< 0.1%
_XV_ug_IUiJrGfMiJUqz-Q 1
 
< 0.1%
GG4_Idv210PI992wl4Dp_A 1
 
< 0.1%
fNBday9iMr-_VOzPDfP_OQ 1
 
< 0.1%
glAgJz5nTEhPh67IqyBUZg 1
 
< 0.1%
iY3fw3ouBAqglzpjVqQ3DQ 1
 
< 0.1%
9u5_eF46t_8GYd_3xKN5Fw 1
 
< 0.1%
Other values (150336) 150336
> 99.9%

Length

2023-03-07T16:39:50.519331image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pns2l4ensfo8kk83dixa6a 1
 
< 0.1%
jaxmsoinw8poo3xemjt8lq 1
 
< 0.1%
w_amnoi1ig9eay7ncmc67w 1
 
< 0.1%
roeacjqwbeh05rqg7f6tcg 1
 
< 0.1%
8wgisyjyke2tsqn3cdmu8a 1
 
< 0.1%
m0xsshqrasonhgbwdjipqa 1
 
< 0.1%
k0hlbqxx-bt0vf1op7jr1w 1
 
< 0.1%
tufrwirkiki_tansvwinqq 1
 
< 0.1%
mtsw4mcqd7cbvtyjqoe9mw 1
 
< 0.1%
mwmc6_wtde0eubkigxdvfa 1
 
< 0.1%
Other values (150336) 150336
> 99.9%

Most occurring characters

ValueCountFrequency (%)
w 87386
 
2.6%
Q 87120
 
2.6%
g 86959
 
2.6%
A 86939
 
2.6%
z 49726
 
1.5%
6 49706
 
1.5%
2 49695
 
1.5%
t 49689
 
1.5%
f 49630
 
1.5%
k 49626
 
1.5%
Other values (54) 2661136
80.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1358599
41.1%
Uppercase Letter 1356639
41.0%
Decimal Number 494325
 
14.9%
Dash Punctuation 49048
 
1.5%
Connector Punctuation 49001
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 87386
 
6.4%
g 86959
 
6.4%
z 49726
 
3.7%
t 49689
 
3.7%
f 49630
 
3.7%
k 49626
 
3.7%
d 49577
 
3.6%
x 49509
 
3.6%
e 49470
 
3.6%
h 49449
 
3.6%
Other values (16) 787578
58.0%
Uppercase Letter
ValueCountFrequency (%)
Q 87120
 
6.4%
A 86939
 
6.4%
O 49591
 
3.7%
M 49579
 
3.7%
S 49579
 
3.7%
B 49560
 
3.7%
R 49506
 
3.6%
X 49502
 
3.6%
U 49463
 
3.6%
V 49432
 
3.6%
Other values (16) 786368
58.0%
Decimal Number
ValueCountFrequency (%)
6 49706
10.1%
2 49695
10.1%
7 49579
10.0%
0 49498
10.0%
1 49460
10.0%
9 49429
10.0%
3 49351
10.0%
4 49316
10.0%
5 49298
10.0%
8 48993
9.9%
Dash Punctuation
ValueCountFrequency (%)
- 49048
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 49001
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2715238
82.1%
Common 592374
 
17.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 87386
 
3.2%
Q 87120
 
3.2%
g 86959
 
3.2%
A 86939
 
3.2%
z 49726
 
1.8%
t 49689
 
1.8%
f 49630
 
1.8%
k 49626
 
1.8%
O 49591
 
1.8%
M 49579
 
1.8%
Other values (42) 2068993
76.2%
Common
ValueCountFrequency (%)
6 49706
8.4%
2 49695
8.4%
7 49579
8.4%
0 49498
8.4%
1 49460
8.3%
9 49429
8.3%
3 49351
8.3%
4 49316
8.3%
5 49298
8.3%
- 49048
8.3%
Other values (2) 97994
16.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3307612
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 87386
 
2.6%
Q 87120
 
2.6%
g 86959
 
2.6%
A 86939
 
2.6%
z 49726
 
1.5%
6 49706
 
1.5%
2 49695
 
1.5%
t 49689
 
1.5%
f 49630
 
1.5%
k 49626
 
1.5%
Other values (54) 2661136
80.5%

name
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size1.1 MiB

address
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size1.1 MiB

city
Categorical

Distinct1416
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
Philadelphia
14569 
Tucson
 
9250
Tampa
 
9050
Indianapolis
 
7540
Nashville
 
6971
Other values (1411)
102966 

Length

Max length52
Median length29
Mean length9.2428532
Min length3

Characters and Unicode

Total characters1389626
Distinct characters62
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique590 ?
Unique (%)0.4%

Sample

1st rowSanta Barbara
2nd rowAffton
3rd rowTucson
4th rowPhiladelphia
5th rowGreen Lane

Common Values

ValueCountFrequency (%)
Philadelphia 14569
 
9.7%
Tucson 9250
 
6.2%
Tampa 9050
 
6.0%
Indianapolis 7540
 
5.0%
Nashville 6971
 
4.6%
New Orleans 6209
 
4.1%
Reno 5935
 
3.9%
Edmonton 5054
 
3.4%
Saint Louis 4827
 
3.2%
Santa Barbara 3829
 
2.5%
Other values (1406) 77112
51.3%

Length

2023-03-07T16:39:50.565787image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
philadelphia 14586
 
7.6%
tucson 9273
 
4.8%
tampa 9225
 
4.8%
indianapolis 7548
 
3.9%
new 7334
 
3.8%
saint 7017
 
3.7%
nashville 6987
 
3.7%
louis 6490
 
3.4%
orleans 6217
 
3.2%
reno 5945
 
3.1%
Other values (1062) 110704
57.9%

Most occurring characters

ValueCountFrequency (%)
a 148933
 
10.7%
e 118641
 
8.5%
i 109094
 
7.9%
n 106165
 
7.6%
l 103560
 
7.5%
o 86646
 
6.2%
r 74166
 
5.3%
s 68576
 
4.9%
t 55713
 
4.0%
h 49379
 
3.6%
Other values (52) 468753
33.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1153369
83.0%
Uppercase Letter 191803
 
13.8%
Space Separator 41038
 
3.0%
Other Punctuation 3300
 
0.2%
Dash Punctuation 101
 
< 0.1%
Open Punctuation 6
 
< 0.1%
Close Punctuation 6
 
< 0.1%
Format 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 148933
12.9%
e 118641
10.3%
i 109094
9.5%
n 106165
9.2%
l 103560
9.0%
o 86646
 
7.5%
r 74166
 
6.4%
s 68576
 
5.9%
t 55713
 
4.8%
h 49379
 
4.3%
Other values (16) 232496
20.2%
Uppercase Letter
ValueCountFrequency (%)
P 24762
12.9%
S 21537
11.2%
T 21152
11.0%
N 16429
 
8.6%
B 13749
 
7.2%
C 11465
 
6.0%
L 10982
 
5.7%
R 8600
 
4.5%
M 8171
 
4.3%
I 8013
 
4.2%
Other values (15) 46943
24.5%
Other Punctuation
ValueCountFrequency (%)
. 2975
90.2%
' 287
 
8.7%
, 26
 
0.8%
& 10
 
0.3%
/ 2
 
0.1%
Space Separator
ValueCountFrequency (%)
41037
> 99.9%
  1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 101
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Format
ValueCountFrequency (%)
​ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1345172
96.8%
Common 44454
 
3.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 148933
 
11.1%
e 118641
 
8.8%
i 109094
 
8.1%
n 106165
 
7.9%
l 103560
 
7.7%
o 86646
 
6.4%
r 74166
 
5.5%
s 68576
 
5.1%
t 55713
 
4.1%
h 49379
 
3.7%
Other values (41) 424299
31.5%
Common
ValueCountFrequency (%)
41037
92.3%
. 2975
 
6.7%
' 287
 
0.6%
- 101
 
0.2%
, 26
 
0.1%
& 10
 
< 0.1%
( 6
 
< 0.1%
) 6
 
< 0.1%
​ 3
 
< 0.1%
/ 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1389622
> 99.9%
Punctuation 3
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 148933
 
10.7%
e 118641
 
8.5%
i 109094
 
7.9%
n 106165
 
7.6%
l 103560
 
7.5%
o 86646
 
6.2%
r 74166
 
5.3%
s 68576
 
4.9%
t 55713
 
4.0%
h 49379
 
3.6%
Other values (50) 468749
33.7%
Punctuation
ValueCountFrequency (%)
​ 3
100.0%
None
ValueCountFrequency (%)
  1
100.0%

state
Categorical

Distinct27
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
PA
34039 
FL
26330 
TN
12056 
IN
11247 
MO
10913 
Other values (22)
55761 

Length

Max length3
Median length2
Mean length2.0000067
Min length2

Characters and Unicode

Total characters300693
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)< 0.1%

Sample

1st rowCA
2nd rowMO
3rd rowAZ
4th rowPA
5th rowPA

Common Values

ValueCountFrequency (%)
PA 34039
22.6%
FL 26330
17.5%
TN 12056
 
8.0%
IN 11247
 
7.5%
MO 10913
 
7.3%
LA 9924
 
6.6%
AZ 9912
 
6.6%
NJ 8536
 
5.7%
NV 7715
 
5.1%
AB 5573
 
3.7%
Other values (17) 14101
9.4%

Length

2023-03-07T16:39:50.611076image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pa 34039
22.6%
fl 26330
17.5%
tn 12056
 
8.0%
in 11247
 
7.5%
mo 10913
 
7.3%
la 9924
 
6.6%
az 9912
 
6.6%
nj 8536
 
5.7%
nv 7715
 
5.1%
ab 5573
 
3.7%
Other values (17) 14101
9.4%

Most occurring characters

ValueCountFrequency (%)
A 64655
21.5%
N 39555
13.2%
L 38399
12.8%
P 34039
11.3%
F 26330
8.8%
I 17863
 
5.9%
T 12063
 
4.0%
M 10918
 
3.6%
O 10916
 
3.6%
Z 9912
 
3.3%
Other values (11) 36043
12.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 300693
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 64655
21.5%
N 39555
13.2%
L 38399
12.8%
P 34039
11.3%
F 26330
8.8%
I 17863
 
5.9%
T 12063
 
4.0%
M 10918
 
3.6%
O 10916
 
3.6%
Z 9912
 
3.3%
Other values (11) 36043
12.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 300693
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 64655
21.5%
N 39555
13.2%
L 38399
12.8%
P 34039
11.3%
F 26330
8.8%
I 17863
 
5.9%
T 12063
 
4.0%
M 10918
 
3.6%
O 10916
 
3.6%
Z 9912
 
3.3%
Other values (11) 36043
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300693
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 64655
21.5%
N 39555
13.2%
L 38399
12.8%
P 34039
11.3%
F 26330
8.8%
I 17863
 
5.9%
T 12063
 
4.0%
M 10918
 
3.6%
O 10916
 
3.6%
Z 9912
 
3.3%
Other values (11) 36043
12.0%

postal_code
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size1.1 MiB

latitude
Real number (ℝ)

Distinct135593
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.67115
Minimum27.555127
Maximum53.679197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2023-03-07T16:39:50.658095image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum27.555127
5-th percentile27.895173
Q132.187293
median38.777413
Q339.954036
95-th percentile43.618147
Maximum53.679197
Range26.12407
Interquartile range (IQR)7.7667427

Descriptive statistics

Standard deviation5.8727589
Coefficient of variation (CV)0.16014657
Kurtosis0.59451944
Mean36.67115
Median Absolute Deviation (MAD)1.5095922
Skewness0.30477456
Sum5513360.7
Variance34.489297
MonotonicityNot monotonic
2023-03-07T16:39:50.706761image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.420334 146
 
0.1%
34.4208305 65
 
< 0.1%
39.4835647 52
 
< 0.1%
27.9552692 35
 
< 0.1%
39.5401545 34
 
< 0.1%
39.4953787 33
 
< 0.1%
39.3831391 32
 
< 0.1%
36.0775432 31
 
< 0.1%
32.2680738 31
 
< 0.1%
39.9531865 31
 
< 0.1%
Other values (135583) 149856
99.7%
ValueCountFrequency (%)
27.555127 1
< 0.1%
27.5582592 1
< 0.1%
27.5616455 1
< 0.1%
27.564137 1
< 0.1%
27.56445724 1
< 0.1%
27.570717 1
< 0.1%
27.578363 1
< 0.1%
27.5786476 1
< 0.1%
27.57870853 1
< 0.1%
27.57947625 1
< 0.1%
ValueCountFrequency (%)
53.6791969 1
< 0.1%
53.656598 1
< 0.1%
53.6518378 1
< 0.1%
53.6497432 1
< 0.1%
53.649735 1
< 0.1%
53.6494895 1
< 0.1%
53.64883738 1
< 0.1%
53.64873411 1
< 0.1%
53.648463 1
< 0.1%
53.647812 1
< 0.1%

longitude
Real number (ℝ)

Distinct131918
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-89.357339
Minimum-120.09514
Maximum-73.200457
Zeros0
Zeros (%)0.0%
Negative150346
Negative (%)100.0%
Memory size1.1 MiB
2023-03-07T16:39:50.756745image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-120.09514
5-th percentile-119.7519
Q1-90.35781
median-86.121179
Q3-75.421542
95-th percentile-75.007048
Maximum-73.200457
Range46.89468
Interquartile range (IQR)14.936268

Descriptive statistics

Standard deviation14.918502
Coefficient of variation (CV)-0.16695329
Kurtosis-0.40968689
Mean-89.357339
Median Absolute Deviation (MAD)10.515837
Skewness-0.98591957
Sum-13434519
Variance222.56169
MonotonicityNot monotonic
2023-03-07T16:39:50.806691image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-119.7107494 146
 
0.1%
-119.7310213 69
 
< 0.1%
-119.6981901 65
 
< 0.1%
-82.4563199 46
 
< 0.1%
-75.1749671 43
 
< 0.1%
-82.2909146 41
 
< 0.1%
-110.8850949 40
 
< 0.1%
-110.9923904 39
 
< 0.1%
-82.6321376 38
 
< 0.1%
-82.7940297 37
 
< 0.1%
Other values (131908) 149782
99.6%
ValueCountFrequency (%)
-120.095137 1
< 0.1%
-120.0924969 1
< 0.1%
-120.0923201 1
< 0.1%
-120.092141 1
< 0.1%
-120.090842 1
< 0.1%
-120.0866753 1
< 0.1%
-120.084046 1
< 0.1%
-120.083748 1
< 0.1%
-120.0837455 1
< 0.1%
-120.0822003 1
< 0.1%
ValueCountFrequency (%)
-73.20045705 1
< 0.1%
-74.6585723 1
< 0.1%
-74.661348 1
< 0.1%
-74.6619316 1
< 0.1%
-74.66445891 1
< 0.1%
-74.666433 1
< 0.1%
-74.6689756 1
< 0.1%
-74.677404 1
< 0.1%
-74.6802499 1
< 0.1%
-74.68259148 1
< 0.1%

stars
Real number (ℝ)

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5967236
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2023-03-07T16:39:50.848160image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3.5
Q34.5
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation0.97442075
Coefficient of variation (CV)0.270919
Kurtosis-0.39744388
Mean3.5967236
Median Absolute Deviation (MAD)0.5
Skewness-0.53713136
Sum540753
Variance0.9494958
MonotonicityNot monotonic
2023-03-07T16:39:50.883987image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
4 31125
20.7%
4.5 27181
18.1%
3.5 26519
17.6%
3 18453
12.3%
5 16307
10.8%
2.5 14316
9.5%
2 9527
 
6.3%
1.5 4932
 
3.3%
1 1986
 
1.3%
ValueCountFrequency (%)
1 1986
 
1.3%
1.5 4932
 
3.3%
2 9527
 
6.3%
2.5 14316
9.5%
3 18453
12.3%
3.5 26519
17.6%
4 31125
20.7%
4.5 27181
18.1%
5 16307
10.8%
ValueCountFrequency (%)
5 16307
10.8%
4.5 27181
18.1%
4 31125
20.7%
3.5 26519
17.6%
3 18453
12.3%
2.5 14316
9.5%
2 9527
 
6.3%
1.5 4932
 
3.3%
1 1986
 
1.3%

review_count
Real number (ℝ)

Distinct1158
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.866561
Minimum5
Maximum7568
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 MiB
2023-03-07T16:39:50.932949image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5
Q18
median15
Q337
95-th percentile173
Maximum7568
Range7563
Interquartile range (IQR)29

Descriptive statistics

Standard deviation121.12014
Coefficient of variation (CV)2.6995636
Kurtosis534.38103
Mean44.866561
Median Absolute Deviation (MAD)9
Skewness16.220577
Sum6745508
Variance14670.087
MonotonicityNot monotonic
2023-03-07T16:39:50.982575image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 14921
 
9.9%
6 11673
 
7.8%
7 9594
 
6.4%
8 8040
 
5.3%
9 6875
 
4.6%
10 5921
 
3.9%
11 5087
 
3.4%
12 4676
 
3.1%
13 4194
 
2.8%
14 3635
 
2.4%
Other values (1148) 75730
50.4%
ValueCountFrequency (%)
5 14921
9.9%
6 11673
7.8%
7 9594
6.4%
8 8040
5.3%
9 6875
4.6%
10 5921
 
3.9%
11 5087
 
3.4%
12 4676
 
3.1%
13 4194
 
2.8%
14 3635
 
2.4%
ValueCountFrequency (%)
7568 1
< 0.1%
7400 1
< 0.1%
6093 1
< 0.1%
5721 1
< 0.1%
5193 1
< 0.1%
5185 1
< 0.1%
5070 1
< 0.1%
4876 1
< 0.1%
4554 1
< 0.1%
4421 1
< 0.1%

is_open
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
1
119698 
0
30648 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters150346
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 119698
79.6%
0 30648
 
20.4%

Length

2023-03-07T16:39:51.029324image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-07T16:39:51.073412image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
1 119698
79.6%
0 30648
 
20.4%

Most occurring characters

ValueCountFrequency (%)
1 119698
79.6%
0 30648
 
20.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 150346
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 119698
79.6%
0 30648
 
20.4%

Most occurring scripts

ValueCountFrequency (%)
Common 150346
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 119698
79.6%
0 30648
 
20.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 150346
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 119698
79.6%
0 30648
 
20.4%

attributes_ByAppointmentOnly
Boolean

Distinct2
Distinct (%)< 0.1%
Missing108047
Missing (%)71.9%
Memory size1.1 MiB
False
26690 
True
15609 
(Missing)
108047 
ValueCountFrequency (%)
False 26690
 
17.8%
True 15609
 
10.4%
(Missing) 108047
71.9%
2023-03-07T16:39:51.111844image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

categories
Categorical

Distinct83160
Distinct (%)55.4%
Missing103
Missing (%)0.1%
Memory size1.1 MiB
Beauty & Spas, Nail Salons
 
1012
Restaurants, Pizza
 
935
Nail Salons, Beauty & Spas
 
934
Pizza, Restaurants
 
823
Restaurants, Mexican
 
728
Other values (83155)
145811 

Length

Max length503
Median length275
Mean length59.269384
Min length4

Characters and Unicode

Total characters8904810
Distinct characters60
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73987 ?
Unique (%)49.2%

Sample

1st rowDoctors, Traditional Chinese Medicine, Naturopathic/Holistic, Acupuncture, Health & Medical, Nutritionists
2nd rowShipping Centers, Local Services, Notaries, Mailbox Centers, Printing Services
3rd rowDepartment Stores, Shopping, Fashion, Home & Garden, Electronics, Furniture Stores
4th rowRestaurants, Food, Bubble Tea, Coffee & Tea, Bakeries
5th rowBrewpubs, Breweries, Food

Common Values

ValueCountFrequency (%)
Beauty & Spas, Nail Salons 1012
 
0.7%
Restaurants, Pizza 935
 
0.6%
Nail Salons, Beauty & Spas 934
 
0.6%
Pizza, Restaurants 823
 
0.5%
Restaurants, Mexican 728
 
0.5%
Restaurants, Chinese 708
 
0.5%
Mexican, Restaurants 672
 
0.4%
Chinese, Restaurants 651
 
0.4%
Food, Coffee & Tea 508
 
0.3%
Beauty & Spas, Hair Salons 493
 
0.3%
Other values (83150) 142779
95.0%

Length

2023-03-07T16:39:51.160456image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
108359
 
9.2%
services 56156
 
4.8%
restaurants 52343
 
4.4%
food 43813
 
3.7%
shopping 24858
 
2.1%
home 24169
 
2.1%
bars 21022
 
1.8%
spas 17070
 
1.5%
beauty 15836
 
1.3%
american 15046
 
1.3%
Other values (1383) 798541
67.8%

Most occurring characters

ValueCountFrequency (%)
1026970
 
11.5%
e 799798
 
9.0%
a 621171
 
7.0%
s 581681
 
6.5%
t 522287
 
5.9%
i 521471
 
5.9%
, 518349
 
5.8%
r 485237
 
5.4%
n 460516
 
5.2%
o 456449
 
5.1%
Other values (50) 2910881
32.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6123488
68.8%
Uppercase Letter 1084193
 
12.2%
Space Separator 1026970
 
11.5%
Other Punctuation 638014
 
7.2%
Open Punctuation 14497
 
0.2%
Close Punctuation 14497
 
0.2%
Dash Punctuation 3146
 
< 0.1%
Decimal Number 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 799798
13.1%
a 621171
10.1%
s 581681
9.5%
t 522287
8.5%
i 521471
8.5%
r 485237
 
7.9%
n 460516
 
7.5%
o 456449
 
7.5%
l 233736
 
3.8%
c 225253
 
3.7%
Other values (16) 1215889
19.9%
Uppercase Letter
ValueCountFrequency (%)
S 202135
18.6%
R 83513
 
7.7%
B 83062
 
7.7%
C 82783
 
7.6%
F 79625
 
7.3%
A 71939
 
6.6%
H 68327
 
6.3%
P 64576
 
6.0%
T 49179
 
4.5%
M 44883
 
4.1%
Other values (15) 254171
23.4%
Other Punctuation
ValueCountFrequency (%)
, 518349
81.2%
& 108359
 
17.0%
/ 6556
 
1.0%
' 4750
 
0.7%
Space Separator
ValueCountFrequency (%)
1026970
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14497
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14497
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3146
100.0%
Decimal Number
ValueCountFrequency (%)
3 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7207681
80.9%
Common 1697129
 
19.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 799798
 
11.1%
a 621171
 
8.6%
s 581681
 
8.1%
t 522287
 
7.2%
i 521471
 
7.2%
r 485237
 
6.7%
n 460516
 
6.4%
o 456449
 
6.3%
l 233736
 
3.2%
c 225253
 
3.1%
Other values (41) 2300082
31.9%
Common
ValueCountFrequency (%)
1026970
60.5%
, 518349
30.5%
& 108359
 
6.4%
( 14497
 
0.9%
) 14497
 
0.9%
/ 6556
 
0.4%
' 4750
 
0.3%
- 3146
 
0.2%
3 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8904810
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1026970
 
11.5%
e 799798
 
9.0%
a 621171
 
7.0%
s 581681
 
6.5%
t 522287
 
5.9%
i 521471
 
5.9%
, 518349
 
5.8%
r 485237
 
5.4%
n 460516
 
5.2%
o 456449
 
5.1%
Other values (50) 2910881
32.7%

attributes_BusinessAcceptsCreditCards
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing30654
Missing (%)20.4%
Memory size1.1 MiB
True
113667 
False
 
6025
(Missing)
30654 
ValueCountFrequency (%)
True 113667
75.6%
False 6025
 
4.0%
(Missing) 30654
 
20.4%
2023-03-07T16:39:51.206180image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

hours_Monday
Categorical

HIGH CARDINALITY  MISSING 

Distinct1315
Distinct (%)1.1%
Missing35872
Missing (%)23.9%
Memory size1.1 MiB
0:0-0:0
31362 
8:0-17:0
 
4202
9:0-17:0
 
3910
11:0-22:0
 
3241
11:0-21:0
 
2938
Other values (1310)
68821 

Length

Max length11
Median length10
Mean length8.1908294
Min length7

Characters and Unicode

Total characters937637
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique458 ?
Unique (%)0.4%

Sample

1st row0:0-0:0
2nd row8:0-22:0
3rd row7:0-20:0
4th row0:0-0:0
5th row0:0-0:0

Common Values

ValueCountFrequency (%)
0:0-0:0 31362
20.9%
8:0-17:0 4202
 
2.8%
9:0-17:0 3910
 
2.6%
11:0-22:0 3241
 
2.2%
11:0-21:0 2938
 
2.0%
9:0-18:0 2599
 
1.7%
10:0-21:0 2278
 
1.5%
10:0-18:0 2186
 
1.5%
8:0-18:0 1884
 
1.3%
10:0-20:0 1733
 
1.2%
Other values (1305) 58141
38.7%
(Missing) 35872
23.9%

Length

2023-03-07T16:39:51.242006image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0:0-0:0 31362
27.4%
8:0-17:0 4202
 
3.7%
9:0-17:0 3910
 
3.4%
11:0-22:0 3241
 
2.8%
11:0-21:0 2938
 
2.6%
9:0-18:0 2599
 
2.3%
10:0-21:0 2278
 
2.0%
10:0-18:0 2186
 
1.9%
8:0-18:0 1884
 
1.6%
10:0-20:0 1733
 
1.5%
Other values (1305) 58141
50.8%

Most occurring characters

ValueCountFrequency (%)
0 317449
33.9%
: 228948
24.4%
- 114474
 
12.2%
1 106371
 
11.3%
2 50734
 
5.4%
3 27397
 
2.9%
9 25330
 
2.7%
8 25003
 
2.7%
7 24768
 
2.6%
6 9321
 
1.0%
Other values (2) 7842
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 594215
63.4%
Other Punctuation 228948
 
24.4%
Dash Punctuation 114474
 
12.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 317449
53.4%
1 106371
 
17.9%
2 50734
 
8.5%
3 27397
 
4.6%
9 25330
 
4.3%
8 25003
 
4.2%
7 24768
 
4.2%
6 9321
 
1.6%
5 5391
 
0.9%
4 2451
 
0.4%
Other Punctuation
ValueCountFrequency (%)
: 228948
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 114474
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 937637
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 317449
33.9%
: 228948
24.4%
- 114474
 
12.2%
1 106371
 
11.3%
2 50734
 
5.4%
3 27397
 
2.9%
9 25330
 
2.7%
8 25003
 
2.7%
7 24768
 
2.6%
6 9321
 
1.0%
Other values (2) 7842
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 937637
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 317449
33.9%
: 228948
24.4%
- 114474
 
12.2%
1 106371
 
11.3%
2 50734
 
5.4%
3 27397
 
2.9%
9 25330
 
2.7%
8 25003
 
2.7%
7 24768
 
2.6%
6 9321
 
1.0%
Other values (2) 7842
 
0.8%

hours_Tuesday
Categorical

HIGH CARDINALITY  MISSING 

Distinct1414
Distinct (%)1.2%
Missing29715
Missing (%)19.8%
Memory size1.1 MiB
0:0-0:0
 
7078
8:0-17:0
 
5232
9:0-17:0
 
4860
11:0-22:0
 
4255
11:0-21:0
 
4193
Other values (1409)
95013 

Length

Max length11
Median length10
Mean length8.5730202
Min length7

Characters and Unicode

Total characters1034172
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique488 ?
Unique (%)0.4%

Sample

1st row8:0-18:30
2nd row8:0-22:0
3rd row7:0-20:0
4th row6:0-22:0
5th row10:0-18:0

Common Values

ValueCountFrequency (%)
0:0-0:0 7078
 
4.7%
8:0-17:0 5232
 
3.5%
9:0-17:0 4860
 
3.2%
11:0-22:0 4255
 
2.8%
11:0-21:0 4193
 
2.8%
9:0-18:0 3868
 
2.6%
10:0-18:0 3578
 
2.4%
10:0-20:0 2742
 
1.8%
8:0-18:0 2719
 
1.8%
10:0-21:0 2695
 
1.8%
Other values (1404) 79411
52.8%
(Missing) 29715
 
19.8%

Length

2023-03-07T16:39:51.288930image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0:0-0:0 7078
 
5.9%
8:0-17:0 5232
 
4.3%
9:0-17:0 4860
 
4.0%
11:0-22:0 4255
 
3.5%
11:0-21:0 4193
 
3.5%
9:0-18:0 3868
 
3.2%
10:0-18:0 3578
 
3.0%
10:0-20:0 2742
 
2.3%
8:0-18:0 2719
 
2.3%
10:0-21:0 2695
 
2.2%
Other values (1404) 79411
65.8%

Most occurring characters

ValueCountFrequency (%)
0 291611
28.2%
: 241262
23.3%
1 149528
14.5%
- 120631
11.7%
2 68196
 
6.6%
3 36204
 
3.5%
9 35001
 
3.4%
8 34838
 
3.4%
7 33466
 
3.2%
6 12513
 
1.2%
Other values (2) 10922
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 672279
65.0%
Other Punctuation 241262
 
23.3%
Dash Punctuation 120631
 
11.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 291611
43.4%
1 149528
22.2%
2 68196
 
10.1%
3 36204
 
5.4%
9 35001
 
5.2%
8 34838
 
5.2%
7 33466
 
5.0%
6 12513
 
1.9%
5 7287
 
1.1%
4 3635
 
0.5%
Other Punctuation
ValueCountFrequency (%)
: 241262
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 120631
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1034172
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 291611
28.2%
: 241262
23.3%
1 149528
14.5%
- 120631
11.7%
2 68196
 
6.6%
3 36204
 
3.5%
9 35001
 
3.4%
8 34838
 
3.4%
7 33466
 
3.2%
6 12513
 
1.2%
Other values (2) 10922
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1034172
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 291611
28.2%
: 241262
23.3%
1 149528
14.5%
- 120631
11.7%
2 68196
 
6.6%
3 36204
 
3.5%
9 35001
 
3.4%
8 34838
 
3.4%
7 33466
 
3.2%
6 12513
 
1.2%
Other values (2) 10922
 
1.1%

hours_Wednesday
Categorical

HIGH CARDINALITY  MISSING 

Distinct1403
Distinct (%)1.1%
Missing26575
Missing (%)17.7%
Memory size1.1 MiB
0:0-0:0
 
7084
8:0-17:0
 
5257
9:0-17:0
 
4824
11:0-21:0
 
4384
11:0-22:0
 
4376
Other values (1398)
97846 

Length

Max length11
Median length10
Mean length8.5815579
Min length7

Characters and Unicode

Total characters1062148
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique459 ?
Unique (%)0.4%

Sample

1st row8:0-18:30
2nd row8:0-22:0
3rd row7:0-20:0
4th row14:0-22:0
5th row6:0-22:0

Common Values

ValueCountFrequency (%)
0:0-0:0 7084
 
4.7%
8:0-17:0 5257
 
3.5%
9:0-17:0 4824
 
3.2%
11:0-21:0 4384
 
2.9%
11:0-22:0 4376
 
2.9%
9:0-18:0 3685
 
2.5%
10:0-18:0 3511
 
2.3%
10:0-21:0 2832
 
1.9%
10:0-19:0 2818
 
1.9%
8:0-18:0 2741
 
1.8%
Other values (1393) 82259
54.7%
(Missing) 26575
 
17.7%

Length

2023-03-07T16:39:51.334876image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0:0-0:0 7084
 
5.7%
8:0-17:0 5257
 
4.2%
9:0-17:0 4824
 
3.9%
11:0-21:0 4384
 
3.5%
11:0-22:0 4376
 
3.5%
9:0-18:0 3685
 
3.0%
10:0-18:0 3511
 
2.8%
10:0-21:0 2832
 
2.3%
10:0-19:0 2818
 
2.3%
8:0-18:0 2741
 
2.2%
Other values (1393) 82259
66.5%

Most occurring characters

ValueCountFrequency (%)
0 298735
28.1%
: 247542
23.3%
1 154427
14.5%
- 123771
11.7%
2 71771
 
6.8%
3 37131
 
3.5%
9 35773
 
3.4%
8 34937
 
3.3%
7 34008
 
3.2%
6 12928
 
1.2%
Other values (2) 11125
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 690835
65.0%
Other Punctuation 247542
 
23.3%
Dash Punctuation 123771
 
11.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 298735
43.2%
1 154427
22.4%
2 71771
 
10.4%
3 37131
 
5.4%
9 35773
 
5.2%
8 34937
 
5.1%
7 34008
 
4.9%
6 12928
 
1.9%
5 7433
 
1.1%
4 3692
 
0.5%
Other Punctuation
ValueCountFrequency (%)
: 247542
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 123771
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1062148
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 298735
28.1%
: 247542
23.3%
1 154427
14.5%
- 123771
11.7%
2 71771
 
6.8%
3 37131
 
3.5%
9 35773
 
3.4%
8 34937
 
3.3%
7 34008
 
3.2%
6 12928
 
1.2%
Other values (2) 11125
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1062148
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 298735
28.1%
: 247542
23.3%
1 154427
14.5%
- 123771
11.7%
2 71771
 
6.8%
3 37131
 
3.5%
9 35773
 
3.4%
8 34937
 
3.3%
7 34008
 
3.2%
6 12928
 
1.2%
Other values (2) 11125
 
1.0%

hours_Thursday
Categorical

HIGH CARDINALITY  MISSING 

Distinct1462
Distinct (%)1.2%
Missing25148
Missing (%)16.7%
Memory size1.1 MiB
0:0-0:0
 
7112
8:0-17:0
 
5209
9:0-17:0
 
4823
11:0-21:0
 
4331
11:0-22:0
 
4273
Other values (1457)
99450 

Length

Max length11
Median length10
Mean length8.5829167
Min length7

Characters and Unicode

Total characters1074564
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique502 ?
Unique (%)0.4%

Sample

1st row8:0-18:30
2nd row8:0-22:0
3rd row7:0-20:0
4th row16:0-22:0
5th row6:0-22:0

Common Values

ValueCountFrequency (%)
0:0-0:0 7112
 
4.7%
8:0-17:0 5209
 
3.5%
9:0-17:0 4823
 
3.2%
11:0-21:0 4331
 
2.9%
11:0-22:0 4273
 
2.8%
9:0-18:0 3604
 
2.4%
10:0-18:0 3447
 
2.3%
10:0-21:0 2851
 
1.9%
10:0-19:0 2837
 
1.9%
10:0-20:0 2747
 
1.8%
Other values (1452) 83964
55.8%
(Missing) 25148
 
16.7%

Length

2023-03-07T16:39:51.381628image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0:0-0:0 7112
 
5.7%
8:0-17:0 5209
 
4.2%
9:0-17:0 4823
 
3.9%
11:0-21:0 4331
 
3.5%
11:0-22:0 4273
 
3.4%
9:0-18:0 3604
 
2.9%
10:0-18:0 3447
 
2.8%
10:0-21:0 2851
 
2.3%
10:0-19:0 2837
 
2.3%
10:0-20:0 2747
 
2.2%
Other values (1452) 83964
67.1%

Most occurring characters

ValueCountFrequency (%)
0 302220
28.1%
: 250396
23.3%
1 156774
14.6%
- 125198
11.7%
2 72182
 
6.7%
3 37688
 
3.5%
9 36134
 
3.4%
8 35105
 
3.3%
7 34237
 
3.2%
6 13191
 
1.2%
Other values (2) 11439
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 698970
65.0%
Other Punctuation 250396
 
23.3%
Dash Punctuation 125198
 
11.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 302220
43.2%
1 156774
22.4%
2 72182
 
10.3%
3 37688
 
5.4%
9 36134
 
5.2%
8 35105
 
5.0%
7 34237
 
4.9%
6 13191
 
1.9%
5 7555
 
1.1%
4 3884
 
0.6%
Other Punctuation
ValueCountFrequency (%)
: 250396
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 125198
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1074564
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 302220
28.1%
: 250396
23.3%
1 156774
14.6%
- 125198
11.7%
2 72182
 
6.7%
3 37688
 
3.5%
9 36134
 
3.4%
8 35105
 
3.3%
7 34237
 
3.2%
6 13191
 
1.2%
Other values (2) 11439
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1074564
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 302220
28.1%
: 250396
23.3%
1 156774
14.6%
- 125198
11.7%
2 72182
 
6.7%
3 37688
 
3.5%
9 36134
 
3.4%
8 35105
 
3.3%
7 34237
 
3.2%
6 13191
 
1.2%
Other values (2) 11439
 
1.1%

hours_Friday
Categorical

HIGH CARDINALITY  MISSING 

Distinct1538
Distinct (%)1.2%
Missing25347
Missing (%)16.9%
Memory size1.1 MiB
0:0-0:0
 
7100
9:0-17:0
 
4984
8:0-17:0
 
4831
9:0-18:0
 
3943
10:0-18:0
 
3850
Other values (1533)
100291 

Length

Max length11
Median length10
Mean length8.5531004
Min length7

Characters and Unicode

Total characters1069129
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique523 ?
Unique (%)0.4%

Sample

1st row8:0-18:30
2nd row8:0-23:0
3rd row7:0-21:0
4th row12:0-22:0
5th row9:0-0:0

Common Values

ValueCountFrequency (%)
0:0-0:0 7100
 
4.7%
9:0-17:0 4984
 
3.3%
8:0-17:0 4831
 
3.2%
9:0-18:0 3943
 
2.6%
10:0-18:0 3850
 
2.6%
11:0-22:0 3744
 
2.5%
11:0-21:0 2824
 
1.9%
11:0-23:0 2710
 
1.8%
8:0-18:0 2664
 
1.8%
10:0-21:0 2610
 
1.7%
Other values (1528) 85739
57.0%
(Missing) 25347
 
16.9%

Length

2023-03-07T16:39:51.428382image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0:0-0:0 7100
 
5.7%
9:0-17:0 4984
 
4.0%
8:0-17:0 4831
 
3.9%
9:0-18:0 3943
 
3.2%
10:0-18:0 3850
 
3.1%
11:0-22:0 3744
 
3.0%
11:0-21:0 2824
 
2.3%
11:0-23:0 2710
 
2.2%
8:0-18:0 2664
 
2.1%
10:0-21:0 2610
 
2.1%
Other values (1528) 85739
68.6%

Most occurring characters

ValueCountFrequency (%)
0 300047
28.1%
: 249998
23.4%
1 153886
14.4%
- 124999
11.7%
2 69334
 
6.5%
3 40921
 
3.8%
8 35666
 
3.3%
9 34959
 
3.3%
7 33921
 
3.2%
6 13151
 
1.2%
Other values (2) 12247
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 694132
64.9%
Other Punctuation 249998
 
23.4%
Dash Punctuation 124999
 
11.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 300047
43.2%
1 153886
22.2%
2 69334
 
10.0%
3 40921
 
5.9%
8 35666
 
5.1%
9 34959
 
5.0%
7 33921
 
4.9%
6 13151
 
1.9%
5 7823
 
1.1%
4 4424
 
0.6%
Other Punctuation
ValueCountFrequency (%)
: 249998
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 124999
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1069129
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 300047
28.1%
: 249998
23.4%
1 153886
14.4%
- 124999
11.7%
2 69334
 
6.5%
3 40921
 
3.8%
8 35666
 
3.3%
9 34959
 
3.3%
7 33921
 
3.2%
6 13151
 
1.2%
Other values (2) 12247
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1069129
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 300047
28.1%
: 249998
23.4%
1 153886
14.4%
- 124999
11.7%
2 69334
 
6.5%
3 40921
 
3.8%
8 35666
 
3.3%
9 34959
 
3.3%
7 33921
 
3.2%
6 13151
 
1.2%
Other values (2) 12247
 
1.1%

hours_Saturday
Categorical

HIGH CARDINALITY  MISSING 

Distinct1439
Distinct (%)1.3%
Missing39576
Missing (%)26.3%
Memory size1.1 MiB
0:0-0:0
 
7156
11:0-22:0
 
3678
9:0-17:0
 
3525
10:0-17:0
 
3276
10:0-18:0
 
3015
Other values (1434)
90120 

Length

Max length11
Median length10
Mean length8.5292769
Min length7

Characters and Unicode

Total characters944788
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique499 ?
Unique (%)0.5%

Sample

1st row8:0-14:0
2nd row8:0-23:0
3rd row7:0-21:0
4th row12:0-22:0
5th row9:0-22:0

Common Values

ValueCountFrequency (%)
0:0-0:0 7156
 
4.8%
11:0-22:0 3678
 
2.4%
9:0-17:0 3525
 
2.3%
10:0-17:0 3276
 
2.2%
10:0-18:0 3015
 
2.0%
11:0-21:0 2679
 
1.8%
11:0-23:0 2624
 
1.7%
9:0-18:0 2608
 
1.7%
10:0-21:0 2502
 
1.7%
8:0-17:0 1987
 
1.3%
Other values (1429) 77720
51.7%
(Missing) 39576
26.3%

Length

2023-03-07T16:39:51.473271image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0:0-0:0 7156
 
6.5%
11:0-22:0 3678
 
3.3%
9:0-17:0 3525
 
3.2%
10:0-17:0 3276
 
3.0%
10:0-18:0 3015
 
2.7%
11:0-21:0 2679
 
2.4%
11:0-23:0 2624
 
2.4%
9:0-18:0 2608
 
2.4%
10:0-21:0 2502
 
2.3%
8:0-17:0 1987
 
1.8%
Other values (1429) 77720
70.2%

Most occurring characters

ValueCountFrequency (%)
0 269834
28.6%
: 221540
23.4%
1 140502
14.9%
- 110770
11.7%
2 67879
 
7.2%
3 32745
 
3.5%
9 29252
 
3.1%
8 24579
 
2.6%
7 22916
 
2.4%
6 11755
 
1.2%
Other values (2) 13016
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 612478
64.8%
Other Punctuation 221540
 
23.4%
Dash Punctuation 110770
 
11.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 269834
44.1%
1 140502
22.9%
2 67879
 
11.1%
3 32745
 
5.3%
9 29252
 
4.8%
8 24579
 
4.0%
7 22916
 
3.7%
6 11755
 
1.9%
5 7653
 
1.2%
4 5363
 
0.9%
Other Punctuation
ValueCountFrequency (%)
: 221540
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 110770
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 944788
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 269834
28.6%
: 221540
23.4%
1 140502
14.9%
- 110770
11.7%
2 67879
 
7.2%
3 32745
 
3.5%
9 29252
 
3.1%
8 24579
 
2.6%
7 22916
 
2.4%
6 11755
 
1.2%
Other values (2) 13016
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 944788
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 269834
28.6%
: 221540
23.4%
1 140502
14.9%
- 110770
11.7%
2 67879
 
7.2%
3 32745
 
3.5%
9 29252
 
3.1%
8 24579
 
2.6%
7 22916
 
2.4%
6 11755
 
1.2%
Other values (2) 13016
 
1.4%

attributes_BikeParking
Boolean

Distinct2
Distinct (%)< 0.1%
Missing77788
Missing (%)51.7%
Memory size1.1 MiB
True
55040 
False
17518 
(Missing)
77788 
ValueCountFrequency (%)
True 55040
36.6%
False 17518
 
11.7%
(Missing) 77788
51.7%
2023-03-07T16:39:51.673021image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_RestaurantsPriceRange2
Categorical

Distinct4
Distinct (%)< 0.1%
Missing65066
Missing (%)43.3%
Memory size1.1 MiB
2.0
48581 
1.0
28840 
3.0
6667 
4.0
 
1192

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters255840
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2.0
2nd row1.0
3rd row1.0
4th row2.0
5th row1.0

Common Values

ValueCountFrequency (%)
2.0 48581
32.3%
1.0 28840
19.2%
3.0 6667
 
4.4%
4.0 1192
 
0.8%
(Missing) 65066
43.3%

Length

2023-03-07T16:39:51.705753image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-07T16:39:51.748200image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
2.0 48581
57.0%
1.0 28840
33.8%
3.0 6667
 
7.8%
4.0 1192
 
1.4%

Most occurring characters

ValueCountFrequency (%)
. 85280
33.3%
0 85280
33.3%
2 48581
19.0%
1 28840
 
11.3%
3 6667
 
2.6%
4 1192
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 170560
66.7%
Other Punctuation 85280
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 85280
50.0%
2 48581
28.5%
1 28840
 
16.9%
3 6667
 
3.9%
4 1192
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 85280
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 255840
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 85280
33.3%
0 85280
33.3%
2 48581
19.0%
1 28840
 
11.3%
3 6667
 
2.6%
4 1192
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 255840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 85280
33.3%
0 85280
33.3%
2 48581
19.0%
1 28840
 
11.3%
3 6667
 
2.6%
4 1192
 
0.5%

attributes_CoatCheck
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing144766
Missing (%)96.3%
Memory size1.1 MiB
False
 
5141
True
 
439
(Missing)
144766 
ValueCountFrequency (%)
False 5141
 
3.4%
True 439
 
0.3%
(Missing) 144766
96.3%
2023-03-07T16:39:51.787516image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_RestaurantsTakeOut
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing92594
Missing (%)61.6%
Memory size1.1 MiB
True
52943 
False
 
4809
(Missing)
92594 
ValueCountFrequency (%)
True 52943
35.2%
False 4809
 
3.2%
(Missing) 92594
61.6%
2023-03-07T16:39:51.820844image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_RestaurantsDelivery
Boolean

Distinct2
Distinct (%)< 0.1%
Missing98012
Missing (%)65.2%
Memory size1.1 MiB
True
32146 
False
20188 
(Missing)
98012 
ValueCountFrequency (%)
True 32146
 
21.4%
False 20188
 
13.4%
(Missing) 98012
65.2%
2023-03-07T16:39:51.854389image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_Caters
Boolean

Distinct2
Distinct (%)< 0.1%
Missing110279
Missing (%)73.4%
Memory size1.1 MiB
True
22337 
False
17730 
(Missing)
110279 
ValueCountFrequency (%)
True 22337
 
14.9%
False 17730
 
11.8%
(Missing) 110279
73.4%
2023-03-07T16:39:51.891807image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_WiFi
Categorical

Distinct3
Distinct (%)< 0.1%
Missing93482
Missing (%)62.2%
Memory size1.1 MiB
free
34414 
no
21831 
paid
 
619

Length

Max length4
Median length4
Mean length3.232168
Min length2

Characters and Unicode

Total characters183794
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowno
2nd rowfree
3rd rowno
4th rowfree
5th rowno

Common Values

ValueCountFrequency (%)
free 34414
 
22.9%
no 21831
 
14.5%
paid 619
 
0.4%
(Missing) 93482
62.2%

Length

2023-03-07T16:39:51.930088image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-07T16:39:51.974972image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
free 34414
60.5%
no 21831
38.4%
paid 619
 
1.1%

Most occurring characters

ValueCountFrequency (%)
e 68828
37.4%
f 34414
18.7%
r 34414
18.7%
n 21831
 
11.9%
o 21831
 
11.9%
p 619
 
0.3%
a 619
 
0.3%
i 619
 
0.3%
d 619
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 183794
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 68828
37.4%
f 34414
18.7%
r 34414
18.7%
n 21831
 
11.9%
o 21831
 
11.9%
p 619
 
0.3%
a 619
 
0.3%
i 619
 
0.3%
d 619
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 183794
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 68828
37.4%
f 34414
18.7%
r 34414
18.7%
n 21831
 
11.9%
o 21831
 
11.9%
p 619
 
0.3%
a 619
 
0.3%
i 619
 
0.3%
d 619
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 183794
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 68828
37.4%
f 34414
18.7%
r 34414
18.7%
n 21831
 
11.9%
o 21831
 
11.9%
p 619
 
0.3%
a 619
 
0.3%
i 619
 
0.3%
d 619
 
0.3%

attributes_BusinessParking_garage
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing63461
Missing (%)42.2%
Memory size1.1 MiB
False
82745 
True
 
4140
(Missing)
63461 
ValueCountFrequency (%)
False 82745
55.0%
True 4140
 
2.8%
(Missing) 63461
42.2%
2023-03-07T16:39:52.012854image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_BusinessParking_street
Boolean

Distinct2
Distinct (%)< 0.1%
Missing64872
Missing (%)43.1%
Memory size1.1 MiB
False
62448 
True
23026 
(Missing)
64872 
ValueCountFrequency (%)
False 62448
41.5%
True 23026
 
15.3%
(Missing) 64872
43.1%
2023-03-07T16:39:52.051536image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_BusinessParking_validated
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing63692
Missing (%)42.4%
Memory size1.1 MiB
False
85815 
True
 
839
(Missing)
63692 
ValueCountFrequency (%)
False 85815
57.1%
True 839
 
0.6%
(Missing) 63692
42.4%
2023-03-07T16:39:52.090060image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_BusinessParking_lot
Boolean

Distinct2
Distinct (%)< 0.1%
Missing63830
Missing (%)42.5%
Memory size1.1 MiB
True
44247 
False
42269 
(Missing)
63830 
ValueCountFrequency (%)
True 44247
29.4%
False 42269
28.1%
(Missing) 63830
42.5%
2023-03-07T16:39:52.128637image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_BusinessParking_valet
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing61551
Missing (%)40.9%
Memory size1.1 MiB
False
87337 
True
 
1458
(Missing)
61551 
ValueCountFrequency (%)
False 87337
58.1%
True 1458
 
1.0%
(Missing) 61551
40.9%
2023-03-07T16:39:52.167382image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_WheelchairAccessible
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing121420
Missing (%)80.8%
Memory size1.1 MiB
True
25993 
False
 
2933
(Missing)
121420 
ValueCountFrequency (%)
True 25993
 
17.3%
False 2933
 
2.0%
(Missing) 121420
80.8%
2023-03-07T16:39:52.204520image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_HappyHour
Boolean

Distinct2
Distinct (%)< 0.1%
Missing135177
Missing (%)89.9%
Memory size1.1 MiB
True
 
9721
False
 
5448
(Missing)
135177 
ValueCountFrequency (%)
True 9721
 
6.5%
False 5448
 
3.6%
(Missing) 135177
89.9%
2023-03-07T16:39:52.241571image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_OutdoorSeating
Boolean

Distinct2
Distinct (%)< 0.1%
Missing103426
Missing (%)68.8%
Memory size1.1 MiB
False
24371 
True
22549 
(Missing)
103426 
ValueCountFrequency (%)
False 24371
 
16.2%
True 22549
 
15.0%
(Missing) 103426
68.8%
2023-03-07T16:39:52.276738image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_HasTV
Boolean

Distinct2
Distinct (%)< 0.1%
Missing105281
Missing (%)70.0%
Memory size1.1 MiB
True
34154 
False
10911 
(Missing)
105281 
ValueCountFrequency (%)
True 34154
 
22.7%
False 10911
 
7.3%
(Missing) 105281
70.0%
2023-03-07T16:39:52.308829image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_RestaurantsReservations
Boolean

Distinct2
Distinct (%)< 0.1%
Missing105387
Missing (%)70.1%
Memory size1.1 MiB
False
30105 
True
14854 
(Missing)
105387 
ValueCountFrequency (%)
False 30105
 
20.0%
True 14854
 
9.9%
(Missing) 105387
70.1%
2023-03-07T16:39:52.345659image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_DogsAllowed
Boolean

Distinct2
Distinct (%)< 0.1%
Missing132088
Missing (%)87.9%
Memory size1.1 MiB
False
 
12267
True
 
5991
(Missing)
132088 
ValueCountFrequency (%)
False 12267
 
8.2%
True 5991
 
4.0%
(Missing) 132088
87.9%
2023-03-07T16:39:52.385528image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

hours_Sunday
Categorical

HIGH CARDINALITY  MISSING 

Distinct1291
Distinct (%)1.6%
Missing69174
Missing (%)46.0%
Memory size1.1 MiB
0:0-0:0
7016 
11:0-21:0
 
3333
11:0-22:0
 
2748
11:0-18:0
 
2376
11:0-17:0
 
2046
Other values (1286)
63653 

Length

Max length11
Median length9
Mean length8.5954393
Min length7

Characters and Unicode

Total characters697709
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique452 ?
Unique (%)0.6%

Sample

1st row8:0-22:0
2nd row7:0-21:0
3rd row12:0-18:0
4th row8:0-22:0
5th row12:0-18:0

Common Values

ValueCountFrequency (%)
0:0-0:0 7016
 
4.7%
11:0-21:0 3333
 
2.2%
11:0-22:0 2748
 
1.8%
11:0-18:0 2376
 
1.6%
11:0-17:0 2046
 
1.4%
12:0-17:0 2026
 
1.3%
10:0-18:0 1820
 
1.2%
12:0-18:0 1777
 
1.2%
9:0-17:0 1634
 
1.1%
10:0-17:0 1610
 
1.1%
Other values (1281) 54786
36.4%
(Missing) 69174
46.0%

Length

2023-03-07T16:39:52.425151image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0:0-0:0 7016
 
8.6%
11:0-21:0 3333
 
4.1%
11:0-22:0 2748
 
3.4%
11:0-18:0 2376
 
2.9%
11:0-17:0 2046
 
2.5%
12:0-17:0 2026
 
2.5%
10:0-18:0 1820
 
2.2%
12:0-18:0 1777
 
2.2%
9:0-17:0 1634
 
2.0%
10:0-17:0 1610
 
2.0%
Other values (1281) 54786
67.5%

Most occurring characters

ValueCountFrequency (%)
0 199911
28.7%
: 162344
23.3%
1 116462
16.7%
- 81172
11.6%
2 56514
 
8.1%
3 18220
 
2.6%
7 16624
 
2.4%
8 15371
 
2.2%
9 13011
 
1.9%
6 8886
 
1.3%
Other values (2) 9194
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 454193
65.1%
Other Punctuation 162344
 
23.3%
Dash Punctuation 81172
 
11.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 199911
44.0%
1 116462
25.6%
2 56514
 
12.4%
3 18220
 
4.0%
7 16624
 
3.7%
8 15371
 
3.4%
9 13011
 
2.9%
6 8886
 
2.0%
5 5537
 
1.2%
4 3657
 
0.8%
Other Punctuation
ValueCountFrequency (%)
: 162344
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81172
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 697709
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 199911
28.7%
: 162344
23.3%
1 116462
16.7%
- 81172
11.6%
2 56514
 
8.1%
3 18220
 
2.6%
7 16624
 
2.4%
8 15371
 
2.2%
9 13011
 
1.9%
6 8886
 
1.3%
Other values (2) 9194
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 697709
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 199911
28.7%
: 162344
23.3%
1 116462
16.7%
- 81172
11.6%
2 56514
 
8.1%
3 18220
 
2.6%
7 16624
 
2.4%
8 15371
 
2.2%
9 13011
 
1.9%
6 8886
 
1.3%
Other values (2) 9194
 
1.3%

attributes_Alcohol
Categorical

Distinct3
Distinct (%)< 0.1%
Missing107195
Missing (%)71.3%
Memory size1.1 MiB
none
20910 
full_bar
15992 
beer_and_wine
6249 

Length

Max length13
Median length8
Mean length6.7857755
Min length4

Characters and Unicode

Total characters292813
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownone
2nd rownone
3rd rowfull_bar
4th rownone
5th rownone

Common Values

ValueCountFrequency (%)
none 20910
 
13.9%
full_bar 15992
 
10.6%
beer_and_wine 6249
 
4.2%
(Missing) 107195
71.3%

Length

2023-03-07T16:39:52.465783image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-07T16:39:52.508375image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
none 20910
48.5%
full_bar 15992
37.1%
beer_and_wine 6249
 
14.5%

Most occurring characters

ValueCountFrequency (%)
n 54318
18.6%
e 39657
13.5%
l 31984
10.9%
_ 28490
9.7%
b 22241
7.6%
a 22241
7.6%
r 22241
7.6%
o 20910
 
7.1%
f 15992
 
5.5%
u 15992
 
5.5%
Other values (3) 18747
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 264323
90.3%
Connector Punctuation 28490
 
9.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 54318
20.5%
e 39657
15.0%
l 31984
12.1%
b 22241
8.4%
a 22241
8.4%
r 22241
8.4%
o 20910
 
7.9%
f 15992
 
6.1%
u 15992
 
6.1%
d 6249
 
2.4%
Other values (2) 12498
 
4.7%
Connector Punctuation
ValueCountFrequency (%)
_ 28490
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 264323
90.3%
Common 28490
 
9.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 54318
20.5%
e 39657
15.0%
l 31984
12.1%
b 22241
8.4%
a 22241
8.4%
r 22241
8.4%
o 20910
 
7.9%
f 15992
 
6.1%
u 15992
 
6.1%
d 6249
 
2.4%
Other values (2) 12498
 
4.7%
Common
ValueCountFrequency (%)
_ 28490
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 292813
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 54318
18.6%
e 39657
13.5%
l 31984
10.9%
_ 28490
9.7%
b 22241
7.6%
a 22241
7.6%
r 22241
7.6%
o 20910
 
7.1%
f 15992
 
5.5%
u 15992
 
5.5%
Other values (3) 18747
 
6.4%

attributes_GoodForKids
Boolean

Distinct2
Distinct (%)< 0.1%
Missing96999
Missing (%)64.5%
Memory size1.1 MiB
True
43905 
False
 
9442
(Missing)
96999 
ValueCountFrequency (%)
True 43905
29.2%
False 9442
 
6.3%
(Missing) 96999
64.5%
2023-03-07T16:39:52.547389image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_RestaurantsAttire
Categorical

IMBALANCE  MISSING 

Distinct3
Distinct (%)< 0.1%
Missing111129
Missing (%)73.9%
Memory size1.1 MiB
casual
38344 
dressy
 
803
formal
 
70

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters235302
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowcasual
2nd rowcasual
3rd rowcasual
4th rowcasual
5th rowcasual

Common Values

ValueCountFrequency (%)
casual 38344
 
25.5%
dressy 803
 
0.5%
formal 70
 
< 0.1%
(Missing) 111129
73.9%

Length

2023-03-07T16:39:52.578402image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-07T16:39:52.621151image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
casual 38344
97.8%
dressy 803
 
2.0%
formal 70
 
0.2%

Most occurring characters

ValueCountFrequency (%)
a 76758
32.6%
s 39950
17.0%
l 38414
16.3%
c 38344
16.3%
u 38344
16.3%
r 873
 
0.4%
d 803
 
0.3%
e 803
 
0.3%
y 803
 
0.3%
f 70
 
< 0.1%
Other values (2) 140
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 235302
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 76758
32.6%
s 39950
17.0%
l 38414
16.3%
c 38344
16.3%
u 38344
16.3%
r 873
 
0.4%
d 803
 
0.3%
e 803
 
0.3%
y 803
 
0.3%
f 70
 
< 0.1%
Other values (2) 140
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 235302
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 76758
32.6%
s 39950
17.0%
l 38414
16.3%
c 38344
16.3%
u 38344
16.3%
r 873
 
0.4%
d 803
 
0.3%
e 803
 
0.3%
y 803
 
0.3%
f 70
 
< 0.1%
Other values (2) 140
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 235302
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 76758
32.6%
s 39950
17.0%
l 38414
16.3%
c 38344
16.3%
u 38344
16.3%
r 873
 
0.4%
d 803
 
0.3%
e 803
 
0.3%
y 803
 
0.3%
f 70
 
< 0.1%
Other values (2) 140
 
0.1%

attributes_RestaurantsTableService
Boolean

Distinct2
Distinct (%)< 0.1%
Missing130379
Missing (%)86.7%
Memory size1.1 MiB
True
 
12674
False
 
7293
(Missing)
130379 
ValueCountFrequency (%)
True 12674
 
8.4%
False 7293
 
4.9%
(Missing) 130379
86.7%
2023-03-07T16:39:52.660251image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_RestaurantsGoodForGroups
Boolean

Distinct2
Distinct (%)< 0.1%
Missing106197
Missing (%)70.6%
Memory size1.1 MiB
True
38148 
False
 
6001
(Missing)
106197 
ValueCountFrequency (%)
True 38148
 
25.4%
False 6001
 
4.0%
(Missing) 106197
70.6%
2023-03-07T16:39:52.699709image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_DriveThru
Boolean

Distinct2
Distinct (%)< 0.1%
Missing143341
Missing (%)95.3%
Memory size1.1 MiB
True
 
4374
False
 
2631
(Missing)
143341 
ValueCountFrequency (%)
True 4374
 
2.9%
False 2631
 
1.7%
(Missing) 143341
95.3%
2023-03-07T16:39:52.737939image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_NoiseLevel
Categorical

Distinct4
Distinct (%)< 0.1%
Missing112392
Missing (%)74.8%
Memory size1.1 MiB
average
26188 
quiet
7634 
loud
2932 
very_loud
 
1200

Length

Max length9
Median length7
Mean length6.4292038
Min length4

Characters and Unicode

Total characters244014
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowaverage
2nd rowaverage
3rd rowaverage
4th rowquiet
5th rowaverage

Common Values

ValueCountFrequency (%)
average 26188
 
17.4%
quiet 7634
 
5.1%
loud 2932
 
2.0%
very_loud 1200
 
0.8%
(Missing) 112392
74.8%

Length

2023-03-07T16:39:52.773656image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-07T16:39:52.817000image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
average 26188
69.0%
quiet 7634
 
20.1%
loud 2932
 
7.7%
very_loud 1200
 
3.2%

Most occurring characters

ValueCountFrequency (%)
e 61210
25.1%
a 52376
21.5%
v 27388
11.2%
r 27388
11.2%
g 26188
10.7%
u 11766
 
4.8%
q 7634
 
3.1%
i 7634
 
3.1%
t 7634
 
3.1%
l 4132
 
1.7%
Other values (4) 10664
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 242814
99.5%
Connector Punctuation 1200
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 61210
25.2%
a 52376
21.6%
v 27388
11.3%
r 27388
11.3%
g 26188
10.8%
u 11766
 
4.8%
q 7634
 
3.1%
i 7634
 
3.1%
t 7634
 
3.1%
l 4132
 
1.7%
Other values (3) 9464
 
3.9%
Connector Punctuation
ValueCountFrequency (%)
_ 1200
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 242814
99.5%
Common 1200
 
0.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 61210
25.2%
a 52376
21.6%
v 27388
11.3%
r 27388
11.3%
g 26188
10.8%
u 11766
 
4.8%
q 7634
 
3.1%
i 7634
 
3.1%
t 7634
 
3.1%
l 4132
 
1.7%
Other values (3) 9464
 
3.9%
Common
ValueCountFrequency (%)
_ 1200
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 244014
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 61210
25.1%
a 52376
21.5%
v 27388
11.2%
r 27388
11.2%
g 26188
10.7%
u 11766
 
4.8%
q 7634
 
3.1%
i 7634
 
3.1%
t 7634
 
3.1%
l 4132
 
1.7%
Other values (4) 10664
 
4.4%

attributes_Ambience_romantic
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing109954
Missing (%)73.1%
Memory size1.1 MiB
False
39698 
True
 
694
(Missing)
109954 
ValueCountFrequency (%)
False 39698
 
26.4%
True 694
 
0.5%
(Missing) 109954
73.1%
2023-03-07T16:39:52.859010image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_Ambience_intimate
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing110860
Missing (%)73.7%
Memory size1.1 MiB
False
38625 
True
 
861
(Missing)
110860 
ValueCountFrequency (%)
False 38625
 
25.7%
True 861
 
0.6%
(Missing) 110860
73.7%
2023-03-07T16:39:52.895805image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_Ambience_touristy
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing110265
Missing (%)73.3%
Memory size1.1 MiB
False
39764 
True
 
317
(Missing)
110265 
ValueCountFrequency (%)
False 39764
 
26.4%
True 317
 
0.2%
(Missing) 110265
73.3%
2023-03-07T16:39:52.933610image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_Ambience_hipster
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing111021
Missing (%)73.8%
Memory size1.1 MiB
False
38207 
True
 
1118
(Missing)
111021 
ValueCountFrequency (%)
False 38207
 
25.4%
True 1118
 
0.7%
(Missing) 111021
73.8%
2023-03-07T16:39:52.970536image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_Ambience_divey
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing112075
Missing (%)74.5%
Memory size1.1 MiB
False
36803 
True
 
1468
(Missing)
112075 
ValueCountFrequency (%)
False 36803
 
24.5%
True 1468
 
1.0%
(Missing) 112075
74.5%
2023-03-07T16:39:53.007544image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_Ambience_classy
Boolean

Distinct2
Distinct (%)< 0.1%
Missing110211
Missing (%)73.3%
Memory size1.1 MiB
False
33902 
True
 
6233
(Missing)
110211 
ValueCountFrequency (%)
False 33902
 
22.5%
True 6233
 
4.1%
(Missing) 110211
73.3%
2023-03-07T16:39:53.046090image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_Ambience_trendy
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing111945
Missing (%)74.5%
Memory size1.1 MiB
False
35893 
True
 
2508
(Missing)
111945 
ValueCountFrequency (%)
False 35893
 
23.9%
True 2508
 
1.7%
(Missing) 111945
74.5%
2023-03-07T16:39:53.084624image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_Ambience_upscale
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing109534
Missing (%)72.9%
Memory size1.1 MiB
False
40361 
True
 
451
(Missing)
109534 
ValueCountFrequency (%)
False 40361
 
26.8%
True 451
 
0.3%
(Missing) 109534
72.9%
2023-03-07T16:39:53.121604image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_Ambience_casual
Boolean

Distinct2
Distinct (%)< 0.1%
Missing108832
Missing (%)72.4%
Memory size1.1 MiB
True
20869 
False
20645 
(Missing)
108832 
ValueCountFrequency (%)
True 20869
 
13.9%
False 20645
 
13.7%
(Missing) 108832
72.4%
2023-03-07T16:39:53.160674image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_GoodForMeal_dessert
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing126155
Missing (%)83.9%
Memory size1.1 MiB
False
22413 
True
 
1778
(Missing)
126155 
ValueCountFrequency (%)
False 22413
 
14.9%
True 1778
 
1.2%
(Missing) 126155
83.9%
2023-03-07T16:39:53.195863image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_GoodForMeal_latenight
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing125306
Missing (%)83.3%
Memory size1.1 MiB
False
23709 
True
 
1331
(Missing)
125306 
ValueCountFrequency (%)
False 23709
 
15.8%
True 1331
 
0.9%
(Missing) 125306
83.3%
2023-03-07T16:39:53.303638image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_GoodForMeal_lunch
Boolean

Distinct2
Distinct (%)< 0.1%
Missing123957
Missing (%)82.4%
Memory size1.1 MiB
True
14216 
False
 
12173
(Missing)
123957 
ValueCountFrequency (%)
True 14216
 
9.5%
False 12173
 
8.1%
(Missing) 123957
82.4%
2023-03-07T16:39:53.336742image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_GoodForMeal_dinner
Boolean

Distinct2
Distinct (%)< 0.1%
Missing122914
Missing (%)81.8%
Memory size1.1 MiB
False
14334 
True
13098 
(Missing)
122914 
ValueCountFrequency (%)
False 14334
 
9.5%
True 13098
 
8.7%
(Missing) 122914
81.8%
2023-03-07T16:39:53.371157image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_GoodForMeal_brunch
Boolean

Distinct2
Distinct (%)< 0.1%
Missing125160
Missing (%)83.2%
Memory size1.1 MiB
False
22310 
True
 
2876
(Missing)
125160 
ValueCountFrequency (%)
False 22310
 
14.8%
True 2876
 
1.9%
(Missing) 125160
83.2%
2023-03-07T16:39:53.404873image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_GoodForMeal_breakfast
Boolean

Distinct2
Distinct (%)< 0.1%
Missing124021
Missing (%)82.5%
Memory size1.1 MiB
False
23293 
True
 
3032
(Missing)
124021 
ValueCountFrequency (%)
False 23293
 
15.5%
True 3032
 
2.0%
(Missing) 124021
82.5%
2023-03-07T16:39:53.439675image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_BusinessAcceptsBitcoin
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing132919
Missing (%)88.4%
Memory size1.1 MiB
False
16957 
True
 
470
(Missing)
132919 
ValueCountFrequency (%)
False 16957
 
11.3%
True 470
 
0.3%
(Missing) 132919
88.4%
2023-03-07T16:39:53.477717image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_Smoking
Categorical

Distinct3
Distinct (%)0.1%
Missing145793
Missing (%)97.0%
Memory size1.1 MiB
no
2405 
outdoor
1817 
yes
331 

Length

Max length7
Median length2
Mean length4.068087
Min length2

Characters and Unicode

Total characters18522
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowno
2nd rowno
3rd rowno
4th rowno
5th rowno

Common Values

ValueCountFrequency (%)
no 2405
 
1.6%
outdoor 1817
 
1.2%
yes 331
 
0.2%
(Missing) 145793
97.0%

Length

2023-03-07T16:39:53.511817image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-07T16:39:53.550993image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
no 2405
52.8%
outdoor 1817
39.9%
yes 331
 
7.3%

Most occurring characters

ValueCountFrequency (%)
o 7856
42.4%
n 2405
 
13.0%
u 1817
 
9.8%
t 1817
 
9.8%
d 1817
 
9.8%
r 1817
 
9.8%
y 331
 
1.8%
e 331
 
1.8%
s 331
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 18522
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 7856
42.4%
n 2405
 
13.0%
u 1817
 
9.8%
t 1817
 
9.8%
d 1817
 
9.8%
r 1817
 
9.8%
y 331
 
1.8%
e 331
 
1.8%
s 331
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 18522
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 7856
42.4%
n 2405
 
13.0%
u 1817
 
9.8%
t 1817
 
9.8%
d 1817
 
9.8%
r 1817
 
9.8%
y 331
 
1.8%
e 331
 
1.8%
s 331
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18522
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 7856
42.4%
n 2405
 
13.0%
u 1817
 
9.8%
t 1817
 
9.8%
d 1817
 
9.8%
r 1817
 
9.8%
y 331
 
1.8%
e 331
 
1.8%
s 331
 
1.8%

attributes_Music_dj
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing143632
Missing (%)95.5%
Memory size1.1 MiB
False
 
6358
True
 
356
(Missing)
143632 
ValueCountFrequency (%)
False 6358
 
4.2%
True 356
 
0.2%
(Missing) 143632
95.5%
2023-03-07T16:39:53.586171image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_Music_background_music
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing143278
Missing (%)95.3%
Memory size1.1 MiB
False
 
6866
True
 
202
(Missing)
143278 
ValueCountFrequency (%)
False 6866
 
4.6%
True 202
 
0.1%
(Missing) 143278
95.3%
2023-03-07T16:39:53.624774image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_Music_no_music
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing143488
Missing (%)95.4%
Memory size1.1 MiB
False
 
6858
(Missing)
143488 
ValueCountFrequency (%)
False 6858
 
4.6%
(Missing) 143488
95.4%
2023-03-07T16:39:53.659076image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_Music_jukebox
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing144158
Missing (%)95.9%
Memory size1.1 MiB
False
 
5699
True
 
489
(Missing)
144158 
ValueCountFrequency (%)
False 5699
 
3.8%
True 489
 
0.3%
(Missing) 144158
95.9%
2023-03-07T16:39:53.694491image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_Music_live
Boolean

Distinct2
Distinct (%)< 0.1%
Missing143613
Missing (%)95.5%
Memory size1.1 MiB
False
 
4697
True
 
2036
(Missing)
143613 
ValueCountFrequency (%)
False 4697
 
3.1%
True 2036
 
1.4%
(Missing) 143613
95.5%
2023-03-07T16:39:53.728132image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_Music_video
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing143276
Missing (%)95.3%
Memory size1.1 MiB
False
 
7054
True
 
16
(Missing)
143276 
ValueCountFrequency (%)
False 7054
 
4.7%
True 16
 
< 0.1%
(Missing) 143276
95.3%
2023-03-07T16:39:53.766719image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_Music_karaoke
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing144556
Missing (%)96.1%
Memory size1.1 MiB
False
 
5715
True
 
75
(Missing)
144556 
ValueCountFrequency (%)
False 5715
 
3.8%
True 75
 
< 0.1%
(Missing) 144556
96.1%
2023-03-07T16:39:53.800769image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_GoodForDancing
Boolean

Distinct2
Distinct (%)< 0.1%
Missing145718
Missing (%)96.9%
Memory size1.1 MiB
False
 
3726
True
 
902
(Missing)
145718 
ValueCountFrequency (%)
False 3726
 
2.5%
True 902
 
0.6%
(Missing) 145718
96.9%
2023-03-07T16:39:53.832603image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_AcceptsInsurance
Boolean

Distinct2
Distinct (%)< 0.1%
Missing144641
Missing (%)96.2%
Memory size1.1 MiB
True
 
3938
False
 
1767
(Missing)
144641 
ValueCountFrequency (%)
True 3938
 
2.6%
False 1767
 
1.2%
(Missing) 144641
96.2%
2023-03-07T16:39:53.866910image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_BestNights_monday
Boolean

Distinct2
Distinct (%)< 0.1%
Missing144663
Missing (%)96.2%
Memory size1.1 MiB
False
 
5056
True
 
627
(Missing)
144663 
ValueCountFrequency (%)
False 5056
 
3.4%
True 627
 
0.4%
(Missing) 144663
96.2%
2023-03-07T16:39:53.900614image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_BestNights_tuesday
Boolean

Distinct2
Distinct (%)< 0.1%
Missing144663
Missing (%)96.2%
Memory size1.1 MiB
False
 
4907
True
 
776
(Missing)
144663 
ValueCountFrequency (%)
False 4907
 
3.3%
True 776
 
0.5%
(Missing) 144663
96.2%
2023-03-07T16:39:53.935597image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_BestNights_friday
Boolean

Distinct2
Distinct (%)< 0.1%
Missing144663
Missing (%)96.2%
Memory size1.1 MiB
True
 
3090
False
 
2593
(Missing)
144663 
ValueCountFrequency (%)
True 3090
 
2.1%
False 2593
 
1.7%
(Missing) 144663
96.2%
2023-03-07T16:39:53.969242image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_BestNights_wednesday
Boolean

Distinct2
Distinct (%)< 0.1%
Missing144663
Missing (%)96.2%
Memory size1.1 MiB
False
 
4801
True
 
882
(Missing)
144663 
ValueCountFrequency (%)
False 4801
 
3.2%
True 882
 
0.6%
(Missing) 144663
96.2%
2023-03-07T16:39:54.003703image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_BestNights_thursday
Boolean

Distinct2
Distinct (%)< 0.1%
Missing144663
Missing (%)96.2%
Memory size1.1 MiB
False
 
4149
True
 
1534
(Missing)
144663 
ValueCountFrequency (%)
False 4149
 
2.8%
True 1534
 
1.0%
(Missing) 144663
96.2%
2023-03-07T16:39:54.038861image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_BestNights_sunday
Boolean

Distinct2
Distinct (%)< 0.1%
Missing144663
Missing (%)96.2%
Memory size1.1 MiB
False
 
4913
True
 
770
(Missing)
144663 
ValueCountFrequency (%)
False 4913
 
3.3%
True 770
 
0.5%
(Missing) 144663
96.2%
2023-03-07T16:39:54.072507image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_BestNights_saturday
Boolean

Distinct2
Distinct (%)< 0.1%
Missing144663
Missing (%)96.2%
Memory size1.1 MiB
True
 
3092
False
 
2591
(Missing)
144663 
ValueCountFrequency (%)
True 3092
 
2.1%
False 2591
 
1.7%
(Missing) 144663
96.2%
2023-03-07T16:39:54.107760image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_BYOB
Boolean

Distinct2
Distinct (%)< 0.1%
Missing145907
Missing (%)97.0%
Memory size1.1 MiB
False
 
3437
True
 
1002
(Missing)
145907 
ValueCountFrequency (%)
False 3437
 
2.3%
True 1002
 
0.7%
(Missing) 145907
97.0%
2023-03-07T16:39:54.144537image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_Corkage
Boolean

Distinct2
Distinct (%)0.1%
Missing146804
Missing (%)97.6%
Memory size1.1 MiB
False
 
2446
True
 
1096
(Missing)
146804 
ValueCountFrequency (%)
False 2446
 
1.6%
True 1096
 
0.7%
(Missing) 146804
97.6%
2023-03-07T16:39:54.183581image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_BYOBCorkage
Categorical

Distinct3
Distinct (%)0.2%
Missing148907
Missing (%)99.0%
Memory size1.1 MiB
no
747 
yes_free
590 
yes_corkage
102 

Length

Max length11
Median length2
Mean length5.0979847
Min length2

Characters and Unicode

Total characters7336
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowyes_free
2nd rowno
3rd rowyes_free
4th rowno
5th rowyes_free

Common Values

ValueCountFrequency (%)
no 747
 
0.5%
yes_free 590
 
0.4%
yes_corkage 102
 
0.1%
(Missing) 148907
99.0%

Length

2023-03-07T16:39:54.217713image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-07T16:39:54.261099image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
no 747
51.9%
yes_free 590
41.0%
yes_corkage 102
 
7.1%

Most occurring characters

ValueCountFrequency (%)
e 1974
26.9%
o 849
11.6%
n 747
 
10.2%
y 692
 
9.4%
s 692
 
9.4%
_ 692
 
9.4%
r 692
 
9.4%
f 590
 
8.0%
c 102
 
1.4%
k 102
 
1.4%
Other values (2) 204
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6644
90.6%
Connector Punctuation 692
 
9.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1974
29.7%
o 849
12.8%
n 747
 
11.2%
y 692
 
10.4%
s 692
 
10.4%
r 692
 
10.4%
f 590
 
8.9%
c 102
 
1.5%
k 102
 
1.5%
a 102
 
1.5%
Connector Punctuation
ValueCountFrequency (%)
_ 692
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6644
90.6%
Common 692
 
9.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1974
29.7%
o 849
12.8%
n 747
 
11.2%
y 692
 
10.4%
s 692
 
10.4%
r 692
 
10.4%
f 590
 
8.9%
c 102
 
1.5%
k 102
 
1.5%
a 102
 
1.5%
Common
ValueCountFrequency (%)
_ 692
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7336
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1974
26.9%
o 849
11.6%
n 747
 
10.2%
y 692
 
9.4%
s 692
 
9.4%
_ 692
 
9.4%
r 692
 
9.4%
f 590
 
8.0%
c 102
 
1.4%
k 102
 
1.4%
Other values (2) 204
 
2.8%

attributes_HairSpecializesIn_straightperms
Boolean

Distinct2
Distinct (%)0.2%
Missing149344
Missing (%)99.3%
Memory size1.1 MiB
False
 
675
True
 
327
(Missing)
149344 
ValueCountFrequency (%)
False 675
 
0.4%
True 327
 
0.2%
(Missing) 149344
99.3%
2023-03-07T16:39:54.298051image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_HairSpecializesIn_coloring
Boolean

Distinct2
Distinct (%)0.2%
Missing149311
Missing (%)99.3%
Memory size1.1 MiB
True
 
822
False
 
213
(Missing)
149311 
ValueCountFrequency (%)
True 822
 
0.5%
False 213
 
0.1%
(Missing) 149311
99.3%
2023-03-07T16:39:54.332695image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_HairSpecializesIn_extensions
Boolean

Distinct2
Distinct (%)0.2%
Missing149311
Missing (%)99.3%
Memory size1.1 MiB
True
 
600
False
 
435
(Missing)
149311 
ValueCountFrequency (%)
True 600
 
0.4%
False 435
 
0.3%
(Missing) 149311
99.3%
2023-03-07T16:39:54.366289image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_HairSpecializesIn_africanamerican
Boolean

Distinct2
Distinct (%)0.2%
Missing149344
Missing (%)99.3%
Memory size1.1 MiB
False
 
698
True
 
304
(Missing)
149344 
ValueCountFrequency (%)
False 698
 
0.5%
True 304
 
0.2%
(Missing) 149344
99.3%
2023-03-07T16:39:54.399774image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_HairSpecializesIn_curly
Boolean

Distinct2
Distinct (%)0.2%
Missing149311
Missing (%)99.3%
Memory size1.1 MiB
True
 
734
False
 
301
(Missing)
149311 
ValueCountFrequency (%)
True 734
 
0.5%
False 301
 
0.2%
(Missing) 149311
99.3%
2023-03-07T16:39:54.434374image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_HairSpecializesIn_kids
Boolean

Distinct2
Distinct (%)0.2%
Missing149311
Missing (%)99.3%
Memory size1.1 MiB
False
 
521
True
 
514
(Missing)
149311 
ValueCountFrequency (%)
False 521
 
0.3%
True 514
 
0.3%
(Missing) 149311
99.3%
2023-03-07T16:39:54.467848image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_HairSpecializesIn_perms
Boolean

Distinct2
Distinct (%)0.2%
Missing149311
Missing (%)99.3%
Memory size1.1 MiB
False
 
572
True
 
463
(Missing)
149311 
ValueCountFrequency (%)
False 572
 
0.4%
True 463
 
0.3%
(Missing) 149311
99.3%
2023-03-07T16:39:54.502174image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_HairSpecializesIn_asian
Boolean

Distinct2
Distinct (%)0.2%
Missing149344
Missing (%)99.3%
Memory size1.1 MiB
False
 
596
True
 
406
(Missing)
149344 
ValueCountFrequency (%)
False 596
 
0.4%
True 406
 
0.3%
(Missing) 149344
99.3%
2023-03-07T16:39:54.535717image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_Open24Hours
Boolean

Distinct2
Distinct (%)5.1%
Missing150307
Missing (%)> 99.9%
Memory size1.1 MiB
False
 
20
True
 
19
(Missing)
150307 
ValueCountFrequency (%)
False 20
 
< 0.1%
True 19
 
< 0.1%
(Missing) 150307
> 99.9%
2023-03-07T16:39:54.571356image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_RestaurantsCounterService
Boolean

Distinct2
Distinct (%)10.5%
Missing150327
Missing (%)> 99.9%
Memory size1.1 MiB
True
 
16
False
 
3
(Missing)
150327 
ValueCountFrequency (%)
True 16
 
< 0.1%
False 3
 
< 0.1%
(Missing) 150327
> 99.9%
2023-03-07T16:39:54.610086image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_AgesAllowed
Categorical

Distinct3
Distinct (%)2.3%
Missing150217
Missing (%)99.9%
Memory size1.1 MiB
allages
77 
21plus
46 
18plus
 
6

Length

Max length7
Median length7
Mean length6.5968992
Min length6

Characters and Unicode

Total characters851
Distinct characters10
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row21plus
2nd rowallages
3rd rowallages
4th rowallages
5th rowallages

Common Values

ValueCountFrequency (%)
allages 77
 
0.1%
21plus 46
 
< 0.1%
18plus 6
 
< 0.1%
(Missing) 150217
99.9%

Length

2023-03-07T16:39:54.643470image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-07T16:39:54.687678image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
allages 77
59.7%
21plus 46
35.7%
18plus 6
 
4.7%

Most occurring characters

ValueCountFrequency (%)
l 206
24.2%
a 154
18.1%
s 129
15.2%
g 77
 
9.0%
e 77
 
9.0%
1 52
 
6.1%
p 52
 
6.1%
u 52
 
6.1%
2 46
 
5.4%
8 6
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 747
87.8%
Decimal Number 104
 
12.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 206
27.6%
a 154
20.6%
s 129
17.3%
g 77
 
10.3%
e 77
 
10.3%
p 52
 
7.0%
u 52
 
7.0%
Decimal Number
ValueCountFrequency (%)
1 52
50.0%
2 46
44.2%
8 6
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 747
87.8%
Common 104
 
12.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 206
27.6%
a 154
20.6%
s 129
17.3%
g 77
 
10.3%
e 77
 
10.3%
p 52
 
7.0%
u 52
 
7.0%
Common
ValueCountFrequency (%)
1 52
50.0%
2 46
44.2%
8 6
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 851
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 206
24.2%
a 154
18.1%
s 129
15.2%
g 77
 
9.0%
e 77
 
9.0%
1 52
 
6.1%
p 52
 
6.1%
u 52
 
6.1%
2 46
 
5.4%
8 6
 
0.7%

attributes_DietaryRestrictions_dairy-free
Boolean

Distinct2
Distinct (%)6.7%
Missing150316
Missing (%)> 99.9%
Memory size1.1 MiB
False
 
24
True
 
6
(Missing)
150316 
ValueCountFrequency (%)
False 24
 
< 0.1%
True 6
 
< 0.1%
(Missing) 150316
> 99.9%
2023-03-07T16:39:54.724616image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_DietaryRestrictions_gluten-free
Boolean

Distinct2
Distinct (%)6.7%
Missing150316
Missing (%)> 99.9%
Memory size1.1 MiB
True
 
19
False
 
11
(Missing)
150316 
ValueCountFrequency (%)
True 19
 
< 0.1%
False 11
 
< 0.1%
(Missing) 150316
> 99.9%
2023-03-07T16:39:54.760495image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_DietaryRestrictions_vegan
Boolean

Distinct2
Distinct (%)6.7%
Missing150316
Missing (%)> 99.9%
Memory size1.1 MiB
False
 
16
True
 
14
(Missing)
150316 
ValueCountFrequency (%)
False 16
 
< 0.1%
True 14
 
< 0.1%
(Missing) 150316
> 99.9%
2023-03-07T16:39:54.795380image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_DietaryRestrictions_kosher
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)3.3%
Missing150316
Missing (%)> 99.9%
Memory size1.1 MiB
False
 
30
(Missing)
150316 
ValueCountFrequency (%)
False 30
 
< 0.1%
(Missing) 150316
> 99.9%
2023-03-07T16:39:54.828684image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_DietaryRestrictions_halal
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)6.7%
Missing150316
Missing (%)> 99.9%
Memory size1.1 MiB
False
 
29
True
 
1
(Missing)
150316 
ValueCountFrequency (%)
False 29
 
< 0.1%
True 1
 
< 0.1%
(Missing) 150316
> 99.9%
2023-03-07T16:39:54.863297image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_DietaryRestrictions_soy-free
Boolean

Distinct2
Distinct (%)6.7%
Missing150316
Missing (%)> 99.9%
Memory size1.1 MiB
False
 
26
True
 
4
(Missing)
150316 
ValueCountFrequency (%)
False 26
 
< 0.1%
True 4
 
< 0.1%
(Missing) 150316
> 99.9%
2023-03-07T16:39:54.898751image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

attributes_DietaryRestrictions_vegetarian
Boolean

Distinct2
Distinct (%)6.7%
Missing150316
Missing (%)> 99.9%
Memory size1.1 MiB
True
 
15
False
 
15
(Missing)
150316 
ValueCountFrequency (%)
True 15
 
< 0.1%
False 15
 
< 0.1%
(Missing) 150316
> 99.9%
2023-03-07T16:39:54.934614image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Interactions

2023-03-07T16:39:39.991241image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-07T16:39:39.307040image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-07T16:39:39.584048image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-07T16:39:39.782755image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-07T16:39:40.103091image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-07T16:39:39.371707image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-07T16:39:39.632018image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-07T16:39:39.832198image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-07T16:39:40.151651image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-07T16:39:39.436250image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-07T16:39:39.678090image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-07T16:39:39.882398image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-07T16:39:40.206824image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-07T16:39:39.524843image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-07T16:39:39.732054image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-03-07T16:39:39.936852image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Missing values

2023-03-07T16:39:41.220352image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
A simple visualization of nullity by column.
2023-03-07T16:39:42.725676image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-03-07T16:39:49.081087image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

business_idnameaddresscitystatepostal_codelatitudelongitudestarsreview_countis_openattributes_ByAppointmentOnlycategoriesattributes_BusinessAcceptsCreditCardshours_Mondayhours_Tuesdayhours_Wednesdayhours_Thursdayhours_Fridayhours_Saturdayattributes_BikeParkingattributes_RestaurantsPriceRange2attributes_CoatCheckattributes_RestaurantsTakeOutattributes_RestaurantsDeliveryattributes_Catersattributes_WiFiattributes_BusinessParking_garageattributes_BusinessParking_streetattributes_BusinessParking_validatedattributes_BusinessParking_lotattributes_BusinessParking_valetattributes_WheelchairAccessibleattributes_HappyHourattributes_OutdoorSeatingattributes_HasTVattributes_RestaurantsReservationsattributes_DogsAllowedhours_Sundayattributes_Alcoholattributes_GoodForKidsattributes_RestaurantsAttireattributes_RestaurantsTableServiceattributes_RestaurantsGoodForGroupsattributes_DriveThruattributes_NoiseLevelattributes_Ambience_romanticattributes_Ambience_intimateattributes_Ambience_touristyattributes_Ambience_hipsterattributes_Ambience_diveyattributes_Ambience_classyattributes_Ambience_trendyattributes_Ambience_upscaleattributes_Ambience_casualattributes_GoodForMeal_dessertattributes_GoodForMeal_latenightattributes_GoodForMeal_lunchattributes_GoodForMeal_dinnerattributes_GoodForMeal_brunchattributes_GoodForMeal_breakfastattributes_BusinessAcceptsBitcoinattributes_Smokingattributes_Music_djattributes_Music_background_musicattributes_Music_no_musicattributes_Music_jukeboxattributes_Music_liveattributes_Music_videoattributes_Music_karaokeattributes_GoodForDancingattributes_AcceptsInsuranceattributes_BestNights_mondayattributes_BestNights_tuesdayattributes_BestNights_fridayattributes_BestNights_wednesdayattributes_BestNights_thursdayattributes_BestNights_sundayattributes_BestNights_saturdayattributes_BYOBattributes_Corkageattributes_BYOBCorkageattributes_HairSpecializesIn_straightpermsattributes_HairSpecializesIn_coloringattributes_HairSpecializesIn_extensionsattributes_HairSpecializesIn_africanamericanattributes_HairSpecializesIn_curlyattributes_HairSpecializesIn_kidsattributes_HairSpecializesIn_permsattributes_HairSpecializesIn_asianattributes_Open24Hoursattributes_RestaurantsCounterServiceattributes_AgesAllowedattributes_DietaryRestrictions_dairy-freeattributes_DietaryRestrictions_gluten-freeattributes_DietaryRestrictions_veganattributes_DietaryRestrictions_kosherattributes_DietaryRestrictions_halalattributes_DietaryRestrictions_soy-freeattributes_DietaryRestrictions_vegetarian
0Pns2l4eNsfO8kk83dixA6AAbby Rappoport, LAC, CMQ1616 Chapala St, Ste 2Santa BarbaraCA9310134.426679-119.7111975.070TrueDoctors, Traditional Chinese Medicine, Naturopathic/Holistic, Acupuncture, Health & Medical, NutritionistsNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1mpf3x-BjTdTEA3yCZrAYPwThe UPS Store87 Grasso Plaza Shopping CenterAfftonMO6312338.551126-90.3356953.0151NaNShipping Centers, Local Services, Notaries, Mailbox Centers, Printing ServicesTrue0:0-0:08:0-18:308:0-18:308:0-18:308:0-18:308:0-14:0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
2tUFrWirKiKi_TAnsVWINQQTarget5255 E Broadway BlvdTucsonAZ8571132.223236-110.8804523.5220FalseDepartment Stores, Shopping, Fashion, Home & Garden, Electronics, Furniture StoresTrue8:0-22:08:0-22:08:0-22:08:0-22:08:0-23:08:0-23:0True2.0FalseFalseFalseFalsenoFalseFalseFalseTrueFalseTrueFalseFalseFalseFalseFalse8:0-22:0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
3MTSW4McQd7CbVtyjqoe9mwSt Honore Pastries935 Race StPhiladelphiaPA1910739.955505-75.1555644.0801FalseRestaurants, Food, Bubble Tea, Coffee & Tea, BakeriesFalse7:0-20:07:0-20:07:0-20:07:0-20:07:0-21:07:0-21:0True1.0NaNTrueFalseTruefreeFalseTrueFalseFalseFalseNaNNaNFalseNaNNaNNaN7:0-21:0noneNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
4mWMc6_wTdE0EUBKIGXDVfAPerkiomen Valley Brewery101 Walnut StGreen LanePA1805440.338183-75.4716594.5131NaNBrewpubs, Breweries, FoodTrueNaNNaN14:0-22:016:0-22:012:0-22:012:0-22:0TrueNaNNaNTrueNaNFalseNaNNoneNoneNoneTrueFalseTrueNaNNaNNaNNaNNaN12:0-18:0NaNTrueNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
5CF33F8-E6oudUQ46HnavjQSonic Drive-In615 S Main StAshland CityTN3701536.269593-87.0589432.061FalseBurgers, Fast Food, Sandwiches, Food, Ice Cream & Frozen Yogurt, RestaurantsTrue0:0-0:06:0-22:06:0-22:06:0-22:09:0-0:09:0-22:0False1.0FalseTrueTrueFalsenoNaNNaNNaNNaNNaNTrueFalseTrueTrueFalseFalse8:0-22:0noneTruecasualFalseTrueTrueNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
6n_0UpQx1hsNbnPUSlodU8wFamous Footwear8522 Eager Road, Dierbergs Brentwood PointBrentwoodMO6314438.627695-90.3404652.5131NaNSporting Goods, Fashion, Shoe Stores, Shopping, Sports Wear, AccessoriesTrue0:0-0:010:0-18:010:0-18:010:0-18:010:0-18:010:0-18:0True2.0NaNNaNNaNNaNNaNFalseFalseFalseTrueFalseNaNNaNNaNNaNNaNNaN12:0-18:0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
7qkRM_2X51Yqxk3btlwAQIgTemple Beth-El400 Pasadena Ave SSt. PetersburgFL3370727.766590-82.7329833.551NaNSynagogues, Religious OrganizationsNaN9:0-17:09:0-17:09:0-17:09:0-17:09:0-17:0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
8k0hlBqXX-Bt0vf1op7Jr1wTsevi's Pub And Grill8025 Mackenzie RdAfftonMO6312338.565165-90.3210873.0190NaNPubs, Restaurants, Italian, Bars, American (Traditional), Nightlife, GreekTrueNaNNaNNaNNaNNaNNaNNaN1.0NaNTrueFalseTruefreeFalseFalseFalseTrueFalseNaNNaNTrueTrueFalseNaNNaNfull_barTruecasualNaNTrueNaNaverageFalseFalseFalseFalseFalseFalseFalseFalseFalseNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
9bBDDEgkFA1Otx9Lfe7BZUQSonic Drive-In2312 Dickerson PikeNashvilleTN3720736.208102-86.7681701.5101FalseIce Cream & Frozen Yogurt, Fast Food, Burgers, Restaurants, FoodTrue0:0-0:06:0-21:06:0-21:06:0-16:06:0-16:06:0-17:0NaN1.0FalseTrueTrueFalsenoFalseFalseFalseFalseFalseTrueFalseTrueTrueFalseFalse6:0-21:0noneTruecasualFalseFalseTrueNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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150337x_2IrYgFiQn7GOTTgWRbAwThe Vac & Sew Center200 Haddonfield Berlin Rd, Ste 5VoorheesNJ0804339.857700-74.9872304.050NaNAppliances & Repair, Home & Garden, Appliances, Local Services, ShoppingNaN9:30-18:09:30-18:09:30-18:09:30-18:09:30-18:09:30-17:0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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1503392O2K6SXPWv56amqxCECd4wThe Plum Pit4405 Pennell RdAstonDE1901439.856185-75.4277254.5141NaNRestaurants, Comfort Food, Food, Food Trucks, Caterers, Event Planning & ServicesTrue0:0-0:00:0-0:00:0-0:00:0-0:00:0-0:00:0-0:0True1.0NaNTrueFalseTrueNaNFalseTrueFalseFalseFalseTrueNaNNaNNaNNaNNaN0:0-0:0noneNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFalseNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
150340hn9Toz3s-Ei3uZPt7esExAWest Side Kebab House2470 Guardian Road NWEdmontonABT5T 1K853.509649-113.6759994.5180NaNMiddle Eastern, RestaurantsNaN11:0-22:011:0-22:011:0-22:011:0-22:011:0-22:011:0-22:0NaN2.0NaNTrueNaNNaNNaNFalseFalseFalseFalseFalseNaNNaNNaNNaNNaNNaN11:0-22:0NaNTruecasualTrueTrueNaNaverageFalseFalseFalseFalseNaNFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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150342c8GjPIOTGVmIemT7j5_SyQWild Birds Unlimited2813 Bransford AveNashvilleTN3720436.115118-86.7669254.051NaNPets, Nurseries & Gardening, Pet Stores, Hobby Shops, Bird Shops, Home & Garden, ShoppingTrue9:30-17:309:30-17:309:30-17:309:30-17:309:30-17:309:0-17:0True2.0NaNNaNNaNNaNnoFalseFalseFalseTrueFalseNaNNaNNaNNaNNaNNaN0:0-16:0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
150343_QAMST-NrQobXduilWEqSwClaire's Boutique6020 E 82nd St, Ste 46IndianapolisIN4625039.908707-86.0650883.581NaNShopping, Jewelry, Piercing, Toy Stores, Beauty & Spas, Accessories, FashionTrueNaNNaNNaNNaNNaNNaNNaN1.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
150344mtGm22y5c2UHNXDFAjaPNwCyclery & Fitness Center2472 Troy RdEdwardsvilleIL6202538.782351-89.9505584.0241NaNFitness/Exercise Equipment, Eyewear & Opticians, Shopping, Sporting Goods, BikesTrue9:0-20:09:0-20:09:0-20:09:0-20:09:0-20:09:0-17:0True4.0NaNNoneNoneNaNNaNFalseFalseFalseTrueFalseNaNNaNNaNNaNNaNNaN10:0-17:0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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